Machine Learning Scientist at Sesame | San Francisco

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!

Join our dynamic team at Laurel as a Senior Machine Learning Data Scientist specializing in Analytics. In this pivotal role, you will leverage your expertise in machine learning and data analysis to drive innovative solutions that enhance our decision-making processes. You will collaborate with cross-functional teams to design and implement predictive models, analyze complex datasets, and translate insights into actionable strategies.Your contributions will be key in shaping the future of our analytics framework, enabling us to better serve our clients and stakeholders. If you’re passionate about data science and eager to make a significant impact, we want to hear from you!

Join Hilbert, a pioneering data science-driven growth engine that empowers B2C teams with predictive insights into user behaviors, revenue drivers, and sustainable growth strategies. Our innovative approach compresses lengthy decision-making processes into mere minutes.Trusted by Fortune 10 enterprises and beloved brands like FreshDirect, Blank Street, and Levain Bakery, Hilbert is the backbone of their growth strategies. We are also collaborating with leading AI companies to push the boundaries of what’s possible.We are seeking a talented Data Scientist who possesses a deep understanding of B2C business challenges, develops actionable models using real-world data, and delivers impactful analyses that facilitate significant growth outcomes — all with the initiative and urgency typical of a founder.This is not a role where you simply receive tasks; you will take ownership of problems from start to finish — from problem framing and modeling to measuring impact — for enterprise clients where the stakes are high and feedback is rapid. If you understand the nuances of churn analysis for different sectors, can create effective recommendation systems from sparse data, and can clearly communicate your causal analysis to clients, we want to meet you.ROLE OVERVIEWYou will closely collaborate with the founding team, engineering, product, and go-to-market teams to enhance the data science systems integral to Hilbert. Daily responsibilities include building models, conducting experiments, analyzing data, and producing analyses that influence key decisions. Our focus is B2C, and the challenges we tackle — such as demand forecasting, customer lifecycle management, personalization, and activation — require an individual who can translate business contexts into effective modeling choices. You will thrive in a high-autonomy, high-ambiguity environment where data is often messy, incomplete, or scarce.Key Responsibilities:Develop ML models that enhance core product features: recommendation systems, search relevance, customer segmentation, demand forecasting, and activation optimization.Contribute to configurable, multi-tenant model architectures that adapt to various customer contexts and business needs, avoiding the need for custom solutions for each case.Build effective models using available data — leveraging limited, noisy, or sparse datasets while determining the appropriate level of complexity.Design and implement rigorous A/B tests and recognize when causal inference methods are necessary.

Join Hilberts as a Machine Learning Engineer / Data Scientist in our San Francisco office, where you will leverage cutting-edge technology to drive enterprise-level solutions. You will work collaboratively with cross-functional teams to design, develop, and implement machine learning models that enhance our data-driven decision-making processes.

Join Us as a Founding Data Scientist and Machine Learning EngineerAmplify Your ImpactYou have achieved remarkable milestones in your career—delivering impactful models, influencing key metrics, and showcasing the transformative potential of data science and machine learning. You have positively affected products that touch millions of lives.Now, envision the possibility of enhancing the entire app ecosystem by extending your influence across numerous products and companies, making every app in users’ pockets smarter, more engaging, and indispensable.Your expertise can empower product teams to innovate faster, captivate users, and drive revenue growth, thanks to the intelligence you develop once and deploy universally.We share this ambition; we have successfully achieved it multiple times at leading organizations like Uber, Apple, Meta, Google, and Chime. Our contributions have generated tens of billions of dollars in impacts for essential products relied on by billions, and we are poised to elevate our influence further.If this resonates with the journey you seek, we invite you to continue reading.Our MissionDashboards recount the past; teams require insights for their next move. Palladio AI serves as the intelligence layer between raw data and decisive action, illuminating product opportunities that translate into genuine growth levers and guiding actions so product teams can iterate with confidence and speed rather than wade through noise.Your RoleYou will be part of a team crafting foundational systems in behavioral modeling, causal inference, forecasting, agentic platforms, and beyond. Your contributions will extend these domains: developing ML and AI models to identify and highlight product opportunities, deploying learning loops that enhance with each release. In essence, you will convert fundamental data science principles into a scalable product across various industries.Beyond technical challenges, you will create a platform that aids real people in making informed decisions, transforming data into clarity and clarity into actionable progress.Your ProfilePassion for Craft and Excellence. You dive into complex datasets, prototype swiftly, and refine until insights shine.Impact-Driven Mindset. 6+ years of experience in production ML/DS; you harmonize scientific rigor with a practical approach—“it ships today, iteration follows.”

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 Lyft as a Data Scientist specializing in Machine Learning, Pricing, and Rider Engagement. In this role, you will leverage your expertise in data analysis to improve pricing strategies and enhance rider experiences. Collaborate with cross-functional teams to design, implement, and optimize machine learning models that drive decision-making and business growth.

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.

About FaireFaire is a dynamic online wholesale marketplace dedicated to empowering local businesses. We believe in a future where independent retailers can thrive and compete against retail giants like Walmart and Amazon. By harnessing technology, data, and machine learning, we connect a vibrant community of entrepreneurs globally. Imagine helping your favorite local boutique source outstanding products from around the world to enhance their offerings. Our mission is to provide the tools and insights that enable small businesses to succeed in a competitive landscape.By championing the growth of independent businesses, Faire fosters positive economic impacts within communities worldwide. We are on the lookout for intelligent, resourceful, and passionate individuals to join our team as we drive the shop local movement. If you share our commitment to community, we invite you to be part of ours.About this roleAt Faire, we leverage advanced machine learning and data insights to transform the wholesale industry, enabling local retailers to stand strong against larger competitors. The Data Science team is pivotal in developing and sustaining a variety of algorithms and models that enhance our marketplace. We focus on creating innovative machine learning models that empower our customers to succeed.As a member of the Brand Data Science team focused on Listing Quality, your role will involve enhancing the quality of product listings, enabling retailers to effectively discover and assess products on Faire. You will apply ML and AI to address key challenges, including improving image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. Utilizing deep learning, multi-modal LLMs, and a human-in-the-loop approach, you'll deliver high-performance solutions. In this rapidly evolving domain, you will be at the forefront of applying cutting-edge technology to drive tangible outcomes. You will independently design and implement solutions while collaborating with the cross-functional Listing Quality pod, which includes product, design, engineering, analytics, and operations, to tackle challenges comprehensively.

Join Us in Building a Safer World.At TRM Labs, we are dedicated to providing cutting-edge blockchain analytics and AI solutions that empower law enforcement, national security agencies, financial institutions, and cryptocurrency businesses in the fight against crypto-related fraud and financial crime. Our advanced platforms enable clients to trace the origins and destinations of funds, identify illicit activities, build robust cases, and gain a comprehensive view of potential threats. Trusted by leading agencies and businesses globally, TRM is committed to fostering a safer and more secure world for everyone.We are currently seeking a Full Stack Data Scientist to join our dynamic Knowledge Layer team. This innovative group specializes in extracting, structuring, and analyzing knowledge from vast, unstructured datasets. Positioned at the crossroads of knowledge graphs, entity resolution, graph extraction, and graph analytics, this team plays a pivotal role in enhancing TRM’s core intelligence products.While our team boasts strong backend and graph engineering expertise, we are in search of a candidate who can serve as the voice of machine learning and data science within the team. This individual will bring practical expertise in knowledge extraction and graph-based machine learning to help accelerate and scale our capabilities. This role is perfect for someone who thrives in an end-to-end operational environment, managing everything from model selection and experimentation to the productionization of ML systems and APIs.Your Impact:Design, build, and productionize machine learning models centered on:Knowledge extraction from unstructured data (e.g., Named Entity Recognition, entity linking)Graph-based learning and inferenceEntity resolution and relationship discoveryEvaluate and utilize existing ML models and frameworks to effectively tackle real-world challengesCollaborate closely with backend and graph engineers to integrate ML models into production services and APIsContribute to the design and development of knowledge graphs and ontologiesConduct exploratory data analysis (EDA) to inform modeling decisions and system architectureOversee ML components from inception to deployment, including experimentation, evaluation, and iterative improvementsHelp establish best practices for applied ML within the Knowledge Layer teamQualifications:Proven experience in machine learning, particularly in knowledge extraction and graph-based methodsStrong programming skills in Python or similar languagesFamiliarity with ML frameworks and libraries (e.g., TensorFlow, PyTorch)Experience with data manipulation and analysis tools (e.g., Pandas, NumPy)Excellent communication skills and ability to collaborate effectively with cross-functional teams

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.

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.

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.

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!

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.

At Scale AI, we are the premier partner for data and evaluation in the rapidly evolving field of artificial intelligence. Our commitment to advancing the assessment and benchmarking of large language models (LLMs) positions us at the forefront of AI innovation. We are dedicated to creating leading-edge LLM evaluation methodologies that set new benchmarks for model performance. Our research teams collaborate with the top AI laboratories in the industry to provide high-quality data, accelerate progress in generative AI research, and inform what excellence looks like in this domain. As a Staff Machine Learning Research Scientist on our LLM Evals team, you will spearhead the creation of novel evaluation methodologies, metrics, and benchmarks to assess the strengths and weaknesses of cutting-edge LLMs. Your work will shape our internal strategies and influence the broader AI research community, making this role essential for establishing best practices in data-driven AI development.

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.

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 us at Physical Intelligence as a Research Scientist, where you will be at the forefront of innovation in machine learning and robotics. We are in search of exceptional researchers across all experience levels who demonstrate a strong track record of impactful research results. Ideal candidates will possess a solid foundation in both practical implementation and theoretical frameworks, showcasing a blend of system-building capabilities and significant conceptual, algorithmic, or theoretical advancements. We value diverse backgrounds and encourage applications from both traditional academic researchers and those with unique, unconventional experiences.We are committed to fostering a diverse and inclusive workplace. In accordance with the San Francisco Fair Chance Ordinance, we welcome applications from qualified individuals with arrest and conviction records.