Machine Learning Scientist I Ii Foundation Models For Life Sciences jobs in San Francisco – Browse 1,444 openings on RoboApply Jobs
Machine Learning Scientist I Ii Foundation Models For Life Sciences jobs in San Francisco
Open roles matching “Machine Learning Scientist I Ii Foundation Models For Life Sciences” with location signals for San Francisco. 1,444 active listings on RoboApply Jobs.
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Machine Learning Scientist I / II - Foundation Models for Life Sciences
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Experience Level
Entry Level
Qualifications
We are looking for candidates with a strong foundation in machine learning, statistics, and programming. Ideal candidates will have:A Master's degree or higher in Computer Science, Data Science, or a related field. Experience with deep learning frameworks such as TensorFlow or PyTorch. Proficiency in programming languages such as Python or R. Strong analytical and problem-solving skills. Familiarity with life sciences or healthcare data is a plus.
About the job
Lila Sciences is seeking a Machine Learning Scientist I or II to help shape the development of foundation models designed for life sciences. This position is based in San Francisco, CA.
Role overview
This role focuses on building and refining machine learning models that address challenges in scientific research and healthcare. Collaboration with colleagues from different disciplines is central to the work, supporting the creation of solutions that serve real-world needs in the life sciences sector.
What you will do
Work with cross-functional teams to design and implement machine learning models for life sciences applications.
Contribute to projects that aim to improve scientific research and healthcare outcomes through advanced modeling.
Requirements
Background in machine learning, with interest or experience in life sciences applications.
Ability to collaborate effectively across disciplines.
About Lila Sciences
Lila Sciences is at the forefront of leveraging machine learning to transform the life sciences industry. Our mission is to empower researchers and healthcare professionals with advanced tools that facilitate groundbreaking discoveries. Located in San Francisco, we foster a collaborative and innovative work environment where creativity and technology intersect.
Lila Sciences is seeking a Machine Learning Scientist I or II to help shape the development of foundation models designed for life sciences. This position is based in San Francisco, CA. Role overview This role focuses on building and refining machine learning models that address challenges in scientific research and healthcare. Collaboration with colleagues from different disciplines is central to the work, supporting the creation of solutions that serve real-world needs in the life sciences sector. What you will do Work with cross-functional teams to design and implement machine learning models for life sciences applications. Contribute to projects that aim to improve scientific research and healthcare outcomes through advanced modeling. Requirements Background in machine learning, with interest or experience in life sciences applications. Ability to collaborate effectively across disciplines.
Role overview This Senior or Principal Scientist position at Lila Sciences centers on developing foundation models for life sciences. The role is based in San Francisco, CA. What you will do Lead the design and creation of advanced machine learning models for applications in life sciences. Direct research projects that drive new product development in healthcare and biotechnology. Use expertise in foundation models to address complex challenges within the life sciences field. Impact This role operates at the intersection of machine learning and life sciences, supporting research and products aimed at improving healthcare solutions.
Join Prima MenteAt Prima Mente, we are pioneers in the field of biology-focused artificial intelligence. Our mission is to generate unique datasets, develop versatile biological foundation models, and translate scientific breakthroughs into real-world clinical applications. Our primary focus is on understanding the brain in-depth, safeguarding it from neurological disorders, and enhancing its function during health. Our dynamic team of AI researchers, experimentalists, clinicians, and operational experts are strategically located in London, San Francisco, and Dubai.Your Role: Foundation Models for BiologyAs a Machine Learning Engineer, you will be instrumental in the design, implementation, and scaling of foundational AI models and infrastructure for multi-omics at an unprecedented scale. Your contributions will facilitate significant advancements in scientific comprehension and lead to groundbreaking applications in the medical and biological fields.Key Responsibilities:Develop high-performance machine learning algorithms optimized for large-scale applications, ensuring utmost reliability and efficiency.Design, implement, and maintain comprehensive experimentation pipelines that allow for rapid iterations, precise assessments, and reproducible research results.Refactor and enhance prototype research code into clean, maintainable, and efficient repositories prepared for production-level deployments.Create fast data processing workflows that can effectively manage extensive datasets to expedite research and model development.Engage in experimental design, with a focus on high-impact experiments that yield the greatest signal-to-noise ratio.Growth ExpectationsIn 1 month, you will initiate initial experiments utilizing state-of-the-art machine learning models, review and apply advanced research papers, and enhance existing code for improved efficiency and precision.By 3 months, you will take ownership of a prototype model architecture, showcasing notable algorithmic enhancements, and contribute to methods for large-scale data ingestion and training.Within 6 months, you will have significantly impacted the implementation of a high-performance foundation model, incorporating key algorithmic optimizations that improve scalability and throughput, along with publishing internal benchmarks that demonstrate substantial effects.
The Bot CompanyAt The Bot Company, we are on a mission to create an innovative robotic assistant for every household.Our dynamic team, composed of talented engineers, designers, and operators, is based in San Francisco. We have a rich background from industry leaders such as Tesla, Cruise, OpenAI, Google, and Pixar, and we have successfully delivered products to hundreds of millions of users, honing our ability to create exceptional products and experiences.We pride ourselves on maintaining a streamlined team structure that fosters swift decision-making and minimizes bureaucracy. Each member is considered an Individual Contributor, granted substantial autonomy, ownership, and accountability. Our culture enables us to work across the technology stack with an emphasis on rapid iteration and execution.What We Seek in CandidatesCandidates for all positions at The Bot Company must exhibit remarkable sharpness and the capacity to thrive in high-pressure environments. We expect candidates to showcase:Exceptional Cognitive Abilities: You possess quick thinking, instant learning capabilities, and the ability to reason across diverse domains.Engineering Curiosity: You demonstrate an innate desire to understand how systems function, even beyond your area of expertise.Performance-Driven Attitude: You excel in fast-paced settings, effectively navigate ambiguity, and thrive under demanding circumstances.Machine Learning: Multimodal Foundation ModelsWe are developing unified foundation models capable of reasoning across text, images, video, and kinematics to inform intelligent robotic behaviors.You will engage with large-scale multimodal networks, overseeing the complete process from data handling to model training and deployment.Your ResponsibilitiesConstruct Native Multimodal Policies: Create architectures where vision, language, and other modalities are represented in a unified manner.Enhance Cross-Modal Reasoning: Explore and implement strategies to ensure that the model not only correlates modalities but also comprehends them (e.g., linking visual physics to kinematic constraints).Manage the Training Loop from Start to Finish: Design, execute, troubleshoot, and refine large-scale training experiments; identify failure points, enhance data mixtures, and tighten evaluations to achieve measurable improvements.Deploy and Refine Real Systems: Integrate models into practical robotic frameworks, enhance robot code for model deployment, and optimize performance for edge inference.
Join the Revolution in Behavioral IntelligenceAmplify Your InfluenceYou have achieved remarkable success in your career, creating robust behavioral or neuroscience models that have driven significant outcomes. You possess a talent for discerning patterns in user behavior, comprehending motivations, and optimizing end-to-end user experiences.Now, envision extending your impact across multiple products and organizations, enhancing the entire app ecosystem. Every application at your fingertips becomes smarter, more engaging, and indispensable to its users.Your expertise can empower product teams to innovate more rapidly, delight users, and boost revenue, all thanks to the behavioral intelligence you develop once and deploy universally.We share this vision: our team has accomplished this repeatedly at industry leaders like Uber, Apple, Google, and Chime, generating tens of billions of dollars in value for products vital to billions globally. We are poised to elevate our impact even further.Does this resonate with the next chapter you're seeking? If so, continue reading.Palladio: Pioneering BreakthroughsPalladio AI is an innovative AI platform aimed at transforming product-led growth and enhancing the value our clients provide in users’ daily lives.Our initial focus is on mobile gaming, where development is swift, user engagement is high, and experimentation yields immediate results—making it the perfect testing ground for our platform.Your ContributionsOur team is constructing foundational systems in behavioral modeling, causal inference, forecasting, and agentic platforms. You will play a pivotal role in extending these areas: creating machine learning and AI-driven behavioral models to identify and highlight product opportunities while deploying self-improving learning loops with each iteration. Your work will analyze user sentiments, thoughts, decisions, and actions—translating behavioral insights into opportunities that enhance product intuitiveness, engagement, and rewards. In essence, you will convert first-principles data science, neuroscience, cognitive science, and machine learning into scalable solutions across various industries.Your ProfileUser-Focused. You empathize with users' challenges, needs, and goals throughout their journeys, measure success through user outcomes, and convert insights into innovative and engaging product experiences.Scientific Innovator. You...
Full-time|$251.7K/yr - $330K/yr|On-site|San Francisco Bay Area, CA
Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through innovative cell rejuvenation techniques aimed at reversing diseases, injuries, and disabilities that can arise throughout life.For further insights, please visit our website at altoslabs.com.Our ValueOur singular Altos Value is: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe firmly believe that diverse perspectives are crucial for scientific innovation. At Altos, exceptional scientists and industry leaders collaborate globally to further our shared mission. We prioritize Belonging, ensuring all employees feel valued for their unique perspectives, and we hold ourselves accountable for maintaining a diverse and inclusive environment.Your Contributions to AltosAs a member of our team, you will accelerate and enhance our efforts in developing unified, multi-modal generative foundation models tailored for multiscale biology. You will be a key player in multidisciplinary teams that create the computational platforms essential for Altos to fulfill its mission.In this position, you will collaborate with other scientists and engineers across the Institute of Computation to design, develop, and scale cutting-edge foundation models that address biological inquiries and assist in discovering novel interventions for aging and disease. Your focus will be on synthesizing unstructured multimodal signals with structured relational data and knowledge graphs that depict biological realities.The ideal candidate will excel in a dynamic environment that values teamwork, transparency, scientific excellence, originality, and integrity.
About Plaid Plaid builds tools that help developers create new financial products and experiences. Since 2013, Plaid has connected millions of users to over 12,000 financial institutions across the US, Canada, the UK, and Europe. The company partners with organizations like Venmo, SoFi, Fortune 500 firms, and major banks to make linking financial accounts to apps and services easier. Headquarters are in San Francisco, with offices in New York, Washington D.C., London, and Amsterdam. Team: Data Foundation & AI The Data Foundation and AI team designs and maintains the machine learning and AI infrastructure that supports Plaid’s products. This group transforms Plaid’s financial network data into flexible formats used by teams across the company. Responsibilities span the entire system lifecycle: data curation for pretraining, model development, deployment, serving, and monitoring in production. Role Overview: Senior Machine Learning Engineer (Research Scientist) This position focuses on applied research for Plaid’s foundation model. The Senior Research Scientist leads efforts to design model architectures, set pretraining objectives, and implement fine-tuning strategies that work across a range of product needs. The role also involves building and maintaining production machine learning systems, including training pipelines, model serving, feature engineering, and performance monitoring. Key Responsibilities Design model architectures and define pretraining objectives for Plaid’s foundation model Develop and apply fine-tuning methods for diverse product use cases Build and maintain end-to-end machine learning systems, from data pipelines to model serving Engineer features and monitor system performance in production Create evaluation frameworks to measure model quality across multiple tasks and metrics Location This role is based in San Francisco.
Join latentlabs, a pioneering company at the forefront of biotechnology, as we seek a talented Machine Learning Researcher specializing in generative modeling. You will become part of a dynamic, interdisciplinary team comprising machine learning experts, protein engineers, and biologists, all committed to revolutionizing biological control and disease treatment. In this role, you will design innovative generative models aimed at creating new proteins that exhibit functionality in wet lab assays.
Join our dynamic team at Jobs for Humanity as a Machine Learning Data Scientist, where you will harness the power of data to drive innovative solutions for underserved communities. Your expertise will play a crucial role in developing algorithms and models that enhance accessibility and improve lives.As a key member of our team, you will collaborate with cross-functional teams to identify opportunities for leveraging data to create impactful products. If you are passionate about using your data science skills for a greater good, we want to hear from you!
Full-time|$317.1K/yr - $509.4K/yr|On-site|San Francisco Bay Area, CA;San Diego, CA
Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through advanced cell rejuvenation techniques aimed at reversing diseases, injuries, and age-related disabilities.For more information, please visit our website at altoslabs.com.Our ValueWe embrace a singular value at Altos: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe recognize that diverse perspectives are vital to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders collaborate from around the globe, united by a common mission. Our commitment to fostering a sense of belonging ensures that every employee feels valued for their unique insights. We all share the responsibility of maintaining a diverse and inclusive workplace.What You Will Contribute To AltosAs a Senior or Principal Machine Learning Scientist, you will be pivotal in developing groundbreaking generative AI/ML models that address multi-modal, multiscale biological challenges—from virtual cell simulations to agentic target assessments. We seek an innovative, hands-on individual who thrives in a collaborative and fast-paced environment, emphasizing teamwork, transparency, scientific excellence, originality, rigor, and integrity.
Full-time|$252K/yr - $315K/yr|On-site|San Francisco, CA; Seattle, WA; New York, NY
About Scale AI At Scale AI, we are committed to propelling the advancement of AI technologies. For over eight years, we have been a pioneer in the AI data sector, supporting groundbreaking innovations in areas such as generative AI, defense solutions, and autonomous driving. Following our recent Series F funding round, we are enhancing access to premium data to accelerate the journey towards Artificial General Intelligence (AGI). Building on our legacy of model evaluation for both enterprise and governmental clients, we are expanding our capabilities to establish new benchmarks for evaluations in both public and private domains. About This Role This position is at the leading edge of AI research and practical implementation, concentrating on reasoning within large language models (LLMs). The successful candidate will investigate critical data types vital for evolving LLM-based agents, including browser and software engineering agents. You will significantly influence Scale’s data strategy by pinpointing optimal data sources and methodologies to enhance LLM reasoning. To excel in this role, you will require a profound understanding of LLMs, planning algorithms, and fresh approaches to agentic reasoning, alongside inventive solutions to challenges in data generation, model interaction, and evaluation. Your contributions will lead to transformative research on language model reasoning, facilitate collaboration with external researchers, and engage closely with engineering teams to translate cutting-edge advancements into scalable, real-world applications.
Full-time|$200K/yr - $240K/yr|Hybrid|United States
SentiLink is at the forefront of transforming identity verification and risk management, enabling both institutions and individuals to conduct transactions with confidence. We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our rapid growth reflects the significant traction we've garnered, with our real-time APIs successfully verifying hundreds of millions of identities, especially within the financial services sector, while swiftly expanding into other markets. SentiLink enjoys the backing of top-tier investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We have received accolades from major publications including TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and have consistently ranked on the Forbes Fintech 50 list since 2023. Notably, we made history by being the first company to implement the eCBSV and provided testimony before the United States House of Representatives regarding the future of identity verification.SentiLink promotes a flexible working environment, offering various work arrangements ranging from fully remote to in-office. As a digital-first organization, we emphasize strong collaboration across teams in the U.S. and India. Our offices are located in cities including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram (Delhi) and Bengaluru in India. If you are near any of these locations, we encourage regular in-office engagement. Some positions are designed to be hybrid or in-office. For instance, our engineering team in India primarily operates from our Gurugram office.
Join Arena Intelligence as a Machine Learning ScientistAt Arena Intelligence, we are revolutionizing how AI models are evaluated in real-world scenarios. Founded by innovative researchers from UC Berkeley’s SkyLab, our mission is to push the boundaries of AI evaluation and ensure its practical application.With millions of users engaging with our platform each month, we prioritize community feedback to develop transparent, rigorous, and human-centered model evaluations. Our leaderboards serve as the benchmark for AI performance, gaining the trust of leading enterprises and AI labs to understand the reliability, alignment, and impact of AI systems.Our diverse team comprises experts from esteemed institutions such as UC Berkeley, Google, Stanford, DeepMind, and Discord. We foster a culture that values truth, agility, craftsmanship, curiosity, and impact over hierarchy. We are committed to creating an environment where talented individuals from all backgrounds can excel in their work.Role OverviewWe are seeking a passionate Machine Learning Scientist to spearhead our open-source research initiatives, including the development of open datasets and code releases. You will be instrumental in advancing how AI models are evaluated and understood globally.In this position, you will operationalize our dedication to openness by curating impactful datasets, developing innovative methodologies, and establishing reproducible benchmarks. Your contributions will enhance our public leaderboards, empower community tools, and promote transparency in AI evaluation on a global scale.This interdisciplinary role involves collaboration with engineers, product teams, marketing, and the broader research community to refine model comparisons, analyze preference data, and explore dimensions like style, reasoning, and robustness. You will also work closely with our go-to-market teams to advocate for our open research initiatives, strengthen research partnerships, and encourage community engagement.If you are excited by complex challenges, rigorous evaluation processes, and scientific outreach, we invite you to apply!
About Sygaldry TechnologiesSygaldry Technologies is at the forefront of innovation, developing quantum-accelerated AI servers designed to significantly enhance the speed of AI training and inference. By merging quantum computing with AI, we are navigating the challenges of increasing compute costs and energy constraints, paving the way towards superintelligence. Our AI servers leverage a diverse range of qubit types in a fault-tolerant architecture, achieving the necessary balance of cost, scalability, and speed for advanced AI applications. We are committed to pioneering new frontiers in physics, engineering, and AI, tackling the most complex challenges with a culture grounded in optimism and rigor. We seek individuals passionate about defining the convergence of quantum and AI and making a meaningful global impact.About the RoleGenerative AI is revolutionizing computational possibilities but reveals the limitations of classical hardware. While diffusion models yield remarkable outcomes, their iterative sampling and high-dimensional score estimation often lead to computational inefficiencies.We are convinced that quantum computing holds the key to overcoming these challenges. As an ML Research Scientist, you will operate at the intersection of generative modeling and quantum acceleration, formulating theoretical foundations and practical applications that merge these domains. Your focus will be on identifying areas where quantum methods can deliver substantial advantages in generative workflows, providing not just incremental enhancements but transformative improvements grounded in mathematical principles.Your ResponsibilitiesGenerative Model Architecture & EfficiencyInnovate state-of-the-art diffusion and score-based generative models.Investigate computational bottlenecks in sampling, denoising, and likelihood estimation.Design and evaluate novel solver techniques for diffusion ODEs/SDEs.Quantum-Classical IntegrationDiscover mathematical structures in generative models that are suitable for quantum acceleration.Prototype hybrid workflows that utilize quantum subroutines to enhance classical processes.Conduct rigorous benchmarks comparing theoretical advantages against practical benefits in realistic scenarios.Research to ProductionTransform research findings into scalable implementations.Collaborate with quantum hardware teams to guide architectural specifications.Facilitate the integration of research insights into production environments.
About Wispr FlowAt Wispr Flow, we strive to make device interaction as seamless as conversing with a friend.Wispr Flow has revolutionized voice dictation, now preferred by users over traditional keyboards due to its unparalleled accuracy on the first attempt. Our platform is context-aware, personalized, and effective across all devices, whether desktop or mobile.By 2026, we aim to expand beyond dictation to develop native actions within an agentic framework that comprehends and responds to user needs reliably.Our diverse team comprises AI researchers, designers, growth specialists, and engineers dedicated to reimagining human-computer interaction. We value team members who prioritize open communication, exhibit a user-centric mindset, and pay meticulous attention to detail. Our collaborative environment fosters spirited discussions, truth-seeking, and tangible impact.Having achieved a remarkable 150% revenue growth quarterly for the past year, we have successfully raised $81 million from top-tier venture capitalists and renowned angel investors.
Full-time|$200K/yr - $240K/yr|Hybrid|United States
SentiLink is at the forefront of delivering cutting-edge identity and risk management solutions, providing both individuals and institutions the ability to transact with assurance. We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative approach; our real-time APIs have successfully verified hundreds of millions of identities, initially focusing on the financial sector and quickly expanding into various new markets. SentiLink enjoys the support of prestigious investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We are proud to have received accolades from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and we have been featured in the Forbes Fintech 50 list every year since 2023. Notably, we made history as the first company to deploy the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.SentiLink accommodates a flexible work environment, ranging from fully remote positions to in-office roles. As a digital-first company, we emphasize collaboration across teams in the U.S. and India. We have physical locations in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., alongside offices in Gurugram (Delhi) and Bengaluru in India. For those near our offices, we encourage regular office attendance. Certain roles, such as our engineering team in India, are designed to be primarily in-office.Role Overview:As a Senior Applied ML Scientist at SentiLink, you will be instrumental in developing our core products: advanced models aimed at identifying fraudulent activities while enhancing our expanding array of financial risk solutions. Your expertise as a seasoned researcher will be essential, making you the authoritative figure in your domain. You will frequently engage in high-impact projects that necessitate a profound understanding of the field, critical analytical skills, and robust technical capabilities. Collaboration with various teams across the organization will be key as you investigate new fraud types, innovate product offerings, and conduct analyses to support our sales and marketing efforts.
At Causal Labs, we are on a groundbreaking mission to develop general causal intelligence—artificial intelligence that not only predicts future events but also determines the most effective actions to influence those outcomes.To achieve this monumental goal, we are constructing a Large Physics Foundation Model (LPM). Our focus is on domains governed by physical laws, which inherently exhibit cause-and-effect relationships, setting them apart from traditional visual or textual data.Weather serves as the ideal training environment for our LPM, being one of the most extensively observed physical systems available. It provides immediate, objective feedback from sensory observations and boasts data scales significantly larger than those currently employed to train existing language models.Our team at Causal Labs includes leading researchers and engineers with backgrounds in self-driving technology, drug discovery, and robotics, hailing from prestigious organizations such as Google DeepMind, Cruise, Waymo, Meta, Nabla Bio, and Apple. We firmly believe that achieving general causal intelligence will represent one of the most critical technological advancements for our civilization.We are seeking innovative researchers eager to confront unsolved challenges in the field.This role presents an opportunity to create powerful models rooted in observable feedback and verifiable ground truths. If you possess experience in pioneering research and training large-scale models from the ground up in areas such as language and vision models, robotics, or biology, we invite you to join our mission.
Full-time|$153.6K/yr - $240K/yr|On-site|CA - San Francisco
Employee Applicant Privacy Notice SoFi is a national bank and financial services company that creates mobile-first tools to help people manage their money and reach their financial goals. The team values direct impact and aims to make a positive difference for members. Role overview The Senior Marketing Data Scientist - Machine Learning joins the Marketing Data Science team in San Francisco, CA. This position supports SoFi’s Marketing organization through analytics, model building, experimentation, and performance measurement to help drive marketing and growth initiatives. Work centers on designing, building, and scaling machine learning models that improve customer acquisition, conversion, retention, and lifetime value across SoFi’s products. The role draws on behavioral, transactional, and credit data to create predictive models and actionable insights. Collaboration with cross-functional teams is key for identifying business needs, managing model development end-to-end, implementing models in production, and monitoring their ongoing performance. Regulatory compliance is a consistent focus. Main responsibilities Design, develop, and deploy machine learning models to optimize customer acquisition, onboarding, and engagement for products such as loans, credit cards, investments, and cryptocurrency. Build predictive models for outcomes including customer lifetime value, conversion rates, cross-sell and upsell effectiveness, and retention across channels like email, direct mail, in-app, and Operations. Work with structured and unstructured data, such as behavioral signals, transaction data, and credit attributes, to enable audience segmentation and large-scale personalization. Maintain a feature store to streamline model development. Set up A/B testing frameworks to evaluate marketing strategies and measure their impact.
Join Handshake as a Machine Learning Research Scientist and contribute to groundbreaking projects that leverage advanced algorithms and data analysis to drive innovation. In this role, you will collaborate with a dynamic team to design, implement, and evaluate machine learning models that enhance our products and services. Your expertise will be pivotal in unlocking new insights from data, improving user experiences, and shaping the future of our technology.
Full-time|$250K/yr - $325K/yr|On-site|San Francisco
About World Labs: At World Labs, we create foundational world models capable of perceiving, generating, reasoning, and interacting with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action, reasoning into insight, and imagination into creation. We believe that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical realms. Our world-class team is driven by curiosity and passion, boasting diverse backgrounds in technology, from AI research and systems engineering to product design. This synergy fosters a tight feedback loop between our cutting-edge research and user-empowering products. Role Overview We are seeking an innovative Research Scientist specializing in generative modeling, especially diffusion models, to join our modeling team. This position is ideal for individuals with extensive expertise in applying diffusion models to images, videos, or 3D assets and scenes. While not mandatory, experience in any of the following areas will be considered a significant advantage: Large-scale model trainingResearch in 3D computer vision In this role, you will work closely with researchers, engineers, and product teams to translate advanced 3D modeling and machine learning techniques into practical applications, ensuring our technology stays at the forefront of visual innovation. This position entails substantial hands-on research and engineering work, taking projects from conception to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds. Develop and experiment with large-scale diffusion models to introduce novel control signals, align with target aesthetic preferences, or optimize for efficient inference. Collaborate closely with research and product teams to comprehend and translate product requirements into actionable technical roadmaps. Contribute actively to all phases of model development, including data curation, experimentation, evaluation, and deployment. Continuously investigate and integrate the latest research in diffusion and generative AI. Serve as a key technical resource within the team, mentoring peers and promoting best practices in generative modeling and machine learning engineering.
Lila Sciences is seeking a Machine Learning Scientist I or II to help shape the development of foundation models designed for life sciences. This position is based in San Francisco, CA. Role overview This role focuses on building and refining machine learning models that address challenges in scientific research and healthcare. Collaboration with colleagues from different disciplines is central to the work, supporting the creation of solutions that serve real-world needs in the life sciences sector. What you will do Work with cross-functional teams to design and implement machine learning models for life sciences applications. Contribute to projects that aim to improve scientific research and healthcare outcomes through advanced modeling. Requirements Background in machine learning, with interest or experience in life sciences applications. Ability to collaborate effectively across disciplines.
Role overview This Senior or Principal Scientist position at Lila Sciences centers on developing foundation models for life sciences. The role is based in San Francisco, CA. What you will do Lead the design and creation of advanced machine learning models for applications in life sciences. Direct research projects that drive new product development in healthcare and biotechnology. Use expertise in foundation models to address complex challenges within the life sciences field. Impact This role operates at the intersection of machine learning and life sciences, supporting research and products aimed at improving healthcare solutions.
Join Prima MenteAt Prima Mente, we are pioneers in the field of biology-focused artificial intelligence. Our mission is to generate unique datasets, develop versatile biological foundation models, and translate scientific breakthroughs into real-world clinical applications. Our primary focus is on understanding the brain in-depth, safeguarding it from neurological disorders, and enhancing its function during health. Our dynamic team of AI researchers, experimentalists, clinicians, and operational experts are strategically located in London, San Francisco, and Dubai.Your Role: Foundation Models for BiologyAs a Machine Learning Engineer, you will be instrumental in the design, implementation, and scaling of foundational AI models and infrastructure for multi-omics at an unprecedented scale. Your contributions will facilitate significant advancements in scientific comprehension and lead to groundbreaking applications in the medical and biological fields.Key Responsibilities:Develop high-performance machine learning algorithms optimized for large-scale applications, ensuring utmost reliability and efficiency.Design, implement, and maintain comprehensive experimentation pipelines that allow for rapid iterations, precise assessments, and reproducible research results.Refactor and enhance prototype research code into clean, maintainable, and efficient repositories prepared for production-level deployments.Create fast data processing workflows that can effectively manage extensive datasets to expedite research and model development.Engage in experimental design, with a focus on high-impact experiments that yield the greatest signal-to-noise ratio.Growth ExpectationsIn 1 month, you will initiate initial experiments utilizing state-of-the-art machine learning models, review and apply advanced research papers, and enhance existing code for improved efficiency and precision.By 3 months, you will take ownership of a prototype model architecture, showcasing notable algorithmic enhancements, and contribute to methods for large-scale data ingestion and training.Within 6 months, you will have significantly impacted the implementation of a high-performance foundation model, incorporating key algorithmic optimizations that improve scalability and throughput, along with publishing internal benchmarks that demonstrate substantial effects.
The Bot CompanyAt The Bot Company, we are on a mission to create an innovative robotic assistant for every household.Our dynamic team, composed of talented engineers, designers, and operators, is based in San Francisco. We have a rich background from industry leaders such as Tesla, Cruise, OpenAI, Google, and Pixar, and we have successfully delivered products to hundreds of millions of users, honing our ability to create exceptional products and experiences.We pride ourselves on maintaining a streamlined team structure that fosters swift decision-making and minimizes bureaucracy. Each member is considered an Individual Contributor, granted substantial autonomy, ownership, and accountability. Our culture enables us to work across the technology stack with an emphasis on rapid iteration and execution.What We Seek in CandidatesCandidates for all positions at The Bot Company must exhibit remarkable sharpness and the capacity to thrive in high-pressure environments. We expect candidates to showcase:Exceptional Cognitive Abilities: You possess quick thinking, instant learning capabilities, and the ability to reason across diverse domains.Engineering Curiosity: You demonstrate an innate desire to understand how systems function, even beyond your area of expertise.Performance-Driven Attitude: You excel in fast-paced settings, effectively navigate ambiguity, and thrive under demanding circumstances.Machine Learning: Multimodal Foundation ModelsWe are developing unified foundation models capable of reasoning across text, images, video, and kinematics to inform intelligent robotic behaviors.You will engage with large-scale multimodal networks, overseeing the complete process from data handling to model training and deployment.Your ResponsibilitiesConstruct Native Multimodal Policies: Create architectures where vision, language, and other modalities are represented in a unified manner.Enhance Cross-Modal Reasoning: Explore and implement strategies to ensure that the model not only correlates modalities but also comprehends them (e.g., linking visual physics to kinematic constraints).Manage the Training Loop from Start to Finish: Design, execute, troubleshoot, and refine large-scale training experiments; identify failure points, enhance data mixtures, and tighten evaluations to achieve measurable improvements.Deploy and Refine Real Systems: Integrate models into practical robotic frameworks, enhance robot code for model deployment, and optimize performance for edge inference.
Join the Revolution in Behavioral IntelligenceAmplify Your InfluenceYou have achieved remarkable success in your career, creating robust behavioral or neuroscience models that have driven significant outcomes. You possess a talent for discerning patterns in user behavior, comprehending motivations, and optimizing end-to-end user experiences.Now, envision extending your impact across multiple products and organizations, enhancing the entire app ecosystem. Every application at your fingertips becomes smarter, more engaging, and indispensable to its users.Your expertise can empower product teams to innovate more rapidly, delight users, and boost revenue, all thanks to the behavioral intelligence you develop once and deploy universally.We share this vision: our team has accomplished this repeatedly at industry leaders like Uber, Apple, Google, and Chime, generating tens of billions of dollars in value for products vital to billions globally. We are poised to elevate our impact even further.Does this resonate with the next chapter you're seeking? If so, continue reading.Palladio: Pioneering BreakthroughsPalladio AI is an innovative AI platform aimed at transforming product-led growth and enhancing the value our clients provide in users’ daily lives.Our initial focus is on mobile gaming, where development is swift, user engagement is high, and experimentation yields immediate results—making it the perfect testing ground for our platform.Your ContributionsOur team is constructing foundational systems in behavioral modeling, causal inference, forecasting, and agentic platforms. You will play a pivotal role in extending these areas: creating machine learning and AI-driven behavioral models to identify and highlight product opportunities while deploying self-improving learning loops with each iteration. Your work will analyze user sentiments, thoughts, decisions, and actions—translating behavioral insights into opportunities that enhance product intuitiveness, engagement, and rewards. In essence, you will convert first-principles data science, neuroscience, cognitive science, and machine learning into scalable solutions across various industries.Your ProfileUser-Focused. You empathize with users' challenges, needs, and goals throughout their journeys, measure success through user outcomes, and convert insights into innovative and engaging product experiences.Scientific Innovator. You...
Full-time|$251.7K/yr - $330K/yr|On-site|San Francisco Bay Area, CA
Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through innovative cell rejuvenation techniques aimed at reversing diseases, injuries, and disabilities that can arise throughout life.For further insights, please visit our website at altoslabs.com.Our ValueOur singular Altos Value is: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe firmly believe that diverse perspectives are crucial for scientific innovation. At Altos, exceptional scientists and industry leaders collaborate globally to further our shared mission. We prioritize Belonging, ensuring all employees feel valued for their unique perspectives, and we hold ourselves accountable for maintaining a diverse and inclusive environment.Your Contributions to AltosAs a member of our team, you will accelerate and enhance our efforts in developing unified, multi-modal generative foundation models tailored for multiscale biology. You will be a key player in multidisciplinary teams that create the computational platforms essential for Altos to fulfill its mission.In this position, you will collaborate with other scientists and engineers across the Institute of Computation to design, develop, and scale cutting-edge foundation models that address biological inquiries and assist in discovering novel interventions for aging and disease. Your focus will be on synthesizing unstructured multimodal signals with structured relational data and knowledge graphs that depict biological realities.The ideal candidate will excel in a dynamic environment that values teamwork, transparency, scientific excellence, originality, and integrity.
About Plaid Plaid builds tools that help developers create new financial products and experiences. Since 2013, Plaid has connected millions of users to over 12,000 financial institutions across the US, Canada, the UK, and Europe. The company partners with organizations like Venmo, SoFi, Fortune 500 firms, and major banks to make linking financial accounts to apps and services easier. Headquarters are in San Francisco, with offices in New York, Washington D.C., London, and Amsterdam. Team: Data Foundation & AI The Data Foundation and AI team designs and maintains the machine learning and AI infrastructure that supports Plaid’s products. This group transforms Plaid’s financial network data into flexible formats used by teams across the company. Responsibilities span the entire system lifecycle: data curation for pretraining, model development, deployment, serving, and monitoring in production. Role Overview: Senior Machine Learning Engineer (Research Scientist) This position focuses on applied research for Plaid’s foundation model. The Senior Research Scientist leads efforts to design model architectures, set pretraining objectives, and implement fine-tuning strategies that work across a range of product needs. The role also involves building and maintaining production machine learning systems, including training pipelines, model serving, feature engineering, and performance monitoring. Key Responsibilities Design model architectures and define pretraining objectives for Plaid’s foundation model Develop and apply fine-tuning methods for diverse product use cases Build and maintain end-to-end machine learning systems, from data pipelines to model serving Engineer features and monitor system performance in production Create evaluation frameworks to measure model quality across multiple tasks and metrics Location This role is based in San Francisco.
Join latentlabs, a pioneering company at the forefront of biotechnology, as we seek a talented Machine Learning Researcher specializing in generative modeling. You will become part of a dynamic, interdisciplinary team comprising machine learning experts, protein engineers, and biologists, all committed to revolutionizing biological control and disease treatment. In this role, you will design innovative generative models aimed at creating new proteins that exhibit functionality in wet lab assays.
Join our dynamic team at Jobs for Humanity as a Machine Learning Data Scientist, where you will harness the power of data to drive innovative solutions for underserved communities. Your expertise will play a crucial role in developing algorithms and models that enhance accessibility and improve lives.As a key member of our team, you will collaborate with cross-functional teams to identify opportunities for leveraging data to create impactful products. If you are passionate about using your data science skills for a greater good, we want to hear from you!
Full-time|$317.1K/yr - $509.4K/yr|On-site|San Francisco Bay Area, CA;San Diego, CA
Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through advanced cell rejuvenation techniques aimed at reversing diseases, injuries, and age-related disabilities.For more information, please visit our website at altoslabs.com.Our ValueWe embrace a singular value at Altos: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe recognize that diverse perspectives are vital to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders collaborate from around the globe, united by a common mission. Our commitment to fostering a sense of belonging ensures that every employee feels valued for their unique insights. We all share the responsibility of maintaining a diverse and inclusive workplace.What You Will Contribute To AltosAs a Senior or Principal Machine Learning Scientist, you will be pivotal in developing groundbreaking generative AI/ML models that address multi-modal, multiscale biological challenges—from virtual cell simulations to agentic target assessments. We seek an innovative, hands-on individual who thrives in a collaborative and fast-paced environment, emphasizing teamwork, transparency, scientific excellence, originality, rigor, and integrity.
Full-time|$252K/yr - $315K/yr|On-site|San Francisco, CA; Seattle, WA; New York, NY
About Scale AI At Scale AI, we are committed to propelling the advancement of AI technologies. For over eight years, we have been a pioneer in the AI data sector, supporting groundbreaking innovations in areas such as generative AI, defense solutions, and autonomous driving. Following our recent Series F funding round, we are enhancing access to premium data to accelerate the journey towards Artificial General Intelligence (AGI). Building on our legacy of model evaluation for both enterprise and governmental clients, we are expanding our capabilities to establish new benchmarks for evaluations in both public and private domains. About This Role This position is at the leading edge of AI research and practical implementation, concentrating on reasoning within large language models (LLMs). The successful candidate will investigate critical data types vital for evolving LLM-based agents, including browser and software engineering agents. You will significantly influence Scale’s data strategy by pinpointing optimal data sources and methodologies to enhance LLM reasoning. To excel in this role, you will require a profound understanding of LLMs, planning algorithms, and fresh approaches to agentic reasoning, alongside inventive solutions to challenges in data generation, model interaction, and evaluation. Your contributions will lead to transformative research on language model reasoning, facilitate collaboration with external researchers, and engage closely with engineering teams to translate cutting-edge advancements into scalable, real-world applications.
Full-time|$200K/yr - $240K/yr|Hybrid|United States
SentiLink is at the forefront of transforming identity verification and risk management, enabling both institutions and individuals to conduct transactions with confidence. We are committed to revolutionizing the outdated and inefficient identity verification landscape in the United States, offering solutions that are ten times faster, more intelligent, and more precise.Our rapid growth reflects the significant traction we've garnered, with our real-time APIs successfully verifying hundreds of millions of identities, especially within the financial services sector, while swiftly expanding into other markets. SentiLink enjoys the backing of top-tier investors such as Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We have received accolades from major publications including TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and have consistently ranked on the Forbes Fintech 50 list since 2023. Notably, we made history by being the first company to implement the eCBSV and provided testimony before the United States House of Representatives regarding the future of identity verification.SentiLink promotes a flexible working environment, offering various work arrangements ranging from fully remote to in-office. As a digital-first organization, we emphasize strong collaboration across teams in the U.S. and India. Our offices are located in cities including Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., along with Gurugram (Delhi) and Bengaluru in India. If you are near any of these locations, we encourage regular in-office engagement. Some positions are designed to be hybrid or in-office. For instance, our engineering team in India primarily operates from our Gurugram office.
Join Arena Intelligence as a Machine Learning ScientistAt Arena Intelligence, we are revolutionizing how AI models are evaluated in real-world scenarios. Founded by innovative researchers from UC Berkeley’s SkyLab, our mission is to push the boundaries of AI evaluation and ensure its practical application.With millions of users engaging with our platform each month, we prioritize community feedback to develop transparent, rigorous, and human-centered model evaluations. Our leaderboards serve as the benchmark for AI performance, gaining the trust of leading enterprises and AI labs to understand the reliability, alignment, and impact of AI systems.Our diverse team comprises experts from esteemed institutions such as UC Berkeley, Google, Stanford, DeepMind, and Discord. We foster a culture that values truth, agility, craftsmanship, curiosity, and impact over hierarchy. We are committed to creating an environment where talented individuals from all backgrounds can excel in their work.Role OverviewWe are seeking a passionate Machine Learning Scientist to spearhead our open-source research initiatives, including the development of open datasets and code releases. You will be instrumental in advancing how AI models are evaluated and understood globally.In this position, you will operationalize our dedication to openness by curating impactful datasets, developing innovative methodologies, and establishing reproducible benchmarks. Your contributions will enhance our public leaderboards, empower community tools, and promote transparency in AI evaluation on a global scale.This interdisciplinary role involves collaboration with engineers, product teams, marketing, and the broader research community to refine model comparisons, analyze preference data, and explore dimensions like style, reasoning, and robustness. You will also work closely with our go-to-market teams to advocate for our open research initiatives, strengthen research partnerships, and encourage community engagement.If you are excited by complex challenges, rigorous evaluation processes, and scientific outreach, we invite you to apply!
About Sygaldry TechnologiesSygaldry Technologies is at the forefront of innovation, developing quantum-accelerated AI servers designed to significantly enhance the speed of AI training and inference. By merging quantum computing with AI, we are navigating the challenges of increasing compute costs and energy constraints, paving the way towards superintelligence. Our AI servers leverage a diverse range of qubit types in a fault-tolerant architecture, achieving the necessary balance of cost, scalability, and speed for advanced AI applications. We are committed to pioneering new frontiers in physics, engineering, and AI, tackling the most complex challenges with a culture grounded in optimism and rigor. We seek individuals passionate about defining the convergence of quantum and AI and making a meaningful global impact.About the RoleGenerative AI is revolutionizing computational possibilities but reveals the limitations of classical hardware. While diffusion models yield remarkable outcomes, their iterative sampling and high-dimensional score estimation often lead to computational inefficiencies.We are convinced that quantum computing holds the key to overcoming these challenges. As an ML Research Scientist, you will operate at the intersection of generative modeling and quantum acceleration, formulating theoretical foundations and practical applications that merge these domains. Your focus will be on identifying areas where quantum methods can deliver substantial advantages in generative workflows, providing not just incremental enhancements but transformative improvements grounded in mathematical principles.Your ResponsibilitiesGenerative Model Architecture & EfficiencyInnovate state-of-the-art diffusion and score-based generative models.Investigate computational bottlenecks in sampling, denoising, and likelihood estimation.Design and evaluate novel solver techniques for diffusion ODEs/SDEs.Quantum-Classical IntegrationDiscover mathematical structures in generative models that are suitable for quantum acceleration.Prototype hybrid workflows that utilize quantum subroutines to enhance classical processes.Conduct rigorous benchmarks comparing theoretical advantages against practical benefits in realistic scenarios.Research to ProductionTransform research findings into scalable implementations.Collaborate with quantum hardware teams to guide architectural specifications.Facilitate the integration of research insights into production environments.
About Wispr FlowAt Wispr Flow, we strive to make device interaction as seamless as conversing with a friend.Wispr Flow has revolutionized voice dictation, now preferred by users over traditional keyboards due to its unparalleled accuracy on the first attempt. Our platform is context-aware, personalized, and effective across all devices, whether desktop or mobile.By 2026, we aim to expand beyond dictation to develop native actions within an agentic framework that comprehends and responds to user needs reliably.Our diverse team comprises AI researchers, designers, growth specialists, and engineers dedicated to reimagining human-computer interaction. We value team members who prioritize open communication, exhibit a user-centric mindset, and pay meticulous attention to detail. Our collaborative environment fosters spirited discussions, truth-seeking, and tangible impact.Having achieved a remarkable 150% revenue growth quarterly for the past year, we have successfully raised $81 million from top-tier venture capitalists and renowned angel investors.
Full-time|$200K/yr - $240K/yr|Hybrid|United States
SentiLink is at the forefront of delivering cutting-edge identity and risk management solutions, providing both individuals and institutions the ability to transact with assurance. We are revolutionizing identity verification within the United States, replacing outdated, inefficient, and costly practices with solutions that are ten times faster, smarter, and more precise.Our rapid growth is a testament to our innovative approach; our real-time APIs have successfully verified hundreds of millions of identities, initially focusing on the financial sector and quickly expanding into various new markets. SentiLink enjoys the support of prestigious investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.We are proud to have received accolades from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, and American Banker, and we have been featured in the Forbes Fintech 50 list every year since 2023. Notably, we made history as the first company to deploy the eCBSV and have testified before the United States House of Representatives regarding the future of identity verification.SentiLink accommodates a flexible work environment, ranging from fully remote positions to in-office roles. As a digital-first company, we emphasize collaboration across teams in the U.S. and India. We have physical locations in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., alongside offices in Gurugram (Delhi) and Bengaluru in India. For those near our offices, we encourage regular office attendance. Certain roles, such as our engineering team in India, are designed to be primarily in-office.Role Overview:As a Senior Applied ML Scientist at SentiLink, you will be instrumental in developing our core products: advanced models aimed at identifying fraudulent activities while enhancing our expanding array of financial risk solutions. Your expertise as a seasoned researcher will be essential, making you the authoritative figure in your domain. You will frequently engage in high-impact projects that necessitate a profound understanding of the field, critical analytical skills, and robust technical capabilities. Collaboration with various teams across the organization will be key as you investigate new fraud types, innovate product offerings, and conduct analyses to support our sales and marketing efforts.
At Causal Labs, we are on a groundbreaking mission to develop general causal intelligence—artificial intelligence that not only predicts future events but also determines the most effective actions to influence those outcomes.To achieve this monumental goal, we are constructing a Large Physics Foundation Model (LPM). Our focus is on domains governed by physical laws, which inherently exhibit cause-and-effect relationships, setting them apart from traditional visual or textual data.Weather serves as the ideal training environment for our LPM, being one of the most extensively observed physical systems available. It provides immediate, objective feedback from sensory observations and boasts data scales significantly larger than those currently employed to train existing language models.Our team at Causal Labs includes leading researchers and engineers with backgrounds in self-driving technology, drug discovery, and robotics, hailing from prestigious organizations such as Google DeepMind, Cruise, Waymo, Meta, Nabla Bio, and Apple. We firmly believe that achieving general causal intelligence will represent one of the most critical technological advancements for our civilization.We are seeking innovative researchers eager to confront unsolved challenges in the field.This role presents an opportunity to create powerful models rooted in observable feedback and verifiable ground truths. If you possess experience in pioneering research and training large-scale models from the ground up in areas such as language and vision models, robotics, or biology, we invite you to join our mission.
Full-time|$153.6K/yr - $240K/yr|On-site|CA - San Francisco
Employee Applicant Privacy Notice SoFi is a national bank and financial services company that creates mobile-first tools to help people manage their money and reach their financial goals. The team values direct impact and aims to make a positive difference for members. Role overview The Senior Marketing Data Scientist - Machine Learning joins the Marketing Data Science team in San Francisco, CA. This position supports SoFi’s Marketing organization through analytics, model building, experimentation, and performance measurement to help drive marketing and growth initiatives. Work centers on designing, building, and scaling machine learning models that improve customer acquisition, conversion, retention, and lifetime value across SoFi’s products. The role draws on behavioral, transactional, and credit data to create predictive models and actionable insights. Collaboration with cross-functional teams is key for identifying business needs, managing model development end-to-end, implementing models in production, and monitoring their ongoing performance. Regulatory compliance is a consistent focus. Main responsibilities Design, develop, and deploy machine learning models to optimize customer acquisition, onboarding, and engagement for products such as loans, credit cards, investments, and cryptocurrency. Build predictive models for outcomes including customer lifetime value, conversion rates, cross-sell and upsell effectiveness, and retention across channels like email, direct mail, in-app, and Operations. Work with structured and unstructured data, such as behavioral signals, transaction data, and credit attributes, to enable audience segmentation and large-scale personalization. Maintain a feature store to streamline model development. Set up A/B testing frameworks to evaluate marketing strategies and measure their impact.
Join Handshake as a Machine Learning Research Scientist and contribute to groundbreaking projects that leverage advanced algorithms and data analysis to drive innovation. In this role, you will collaborate with a dynamic team to design, implement, and evaluate machine learning models that enhance our products and services. Your expertise will be pivotal in unlocking new insights from data, improving user experiences, and shaping the future of our technology.
Full-time|$250K/yr - $325K/yr|On-site|San Francisco
About World Labs: At World Labs, we create foundational world models capable of perceiving, generating, reasoning, and interacting with the 3D environment. Our mission is to unlock the full potential of AI through spatial intelligence, transforming perception into action, reasoning into insight, and imagination into creation. We believe that spatial intelligence will revolutionize storytelling, creativity, design, simulation, and immersive experiences across both virtual and physical realms. Our world-class team is driven by curiosity and passion, boasting diverse backgrounds in technology, from AI research and systems engineering to product design. This synergy fosters a tight feedback loop between our cutting-edge research and user-empowering products. Role Overview We are seeking an innovative Research Scientist specializing in generative modeling, especially diffusion models, to join our modeling team. This position is ideal for individuals with extensive expertise in applying diffusion models to images, videos, or 3D assets and scenes. While not mandatory, experience in any of the following areas will be considered a significant advantage: Large-scale model trainingResearch in 3D computer vision In this role, you will work closely with researchers, engineers, and product teams to translate advanced 3D modeling and machine learning techniques into practical applications, ensuring our technology stays at the forefront of visual innovation. This position entails substantial hands-on research and engineering work, taking projects from conception to production deployment. Key Responsibilities Design, implement, and train large-scale diffusion models for generating 3D worlds. Develop and experiment with large-scale diffusion models to introduce novel control signals, align with target aesthetic preferences, or optimize for efficient inference. Collaborate closely with research and product teams to comprehend and translate product requirements into actionable technical roadmaps. Contribute actively to all phases of model development, including data curation, experimentation, evaluation, and deployment. Continuously investigate and integrate the latest research in diffusion and generative AI. Serve as a key technical resource within the team, mentoring peers and promoting best practices in generative modeling and machine learning engineering.
Feb 18, 2026
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