Join Until, a visionary moonshot company dedicated to revolutionizing biology with a groundbreaking 'pause button' for organ preservation. Our immediate mission focuses on organ-scale reversible cryopreservation, which allows for the preservation of donated organs at subzero temperatures while preventing ice formation, facilitating uniform rewarming for transplant. By addressing this monumental challenge, we are paving the way for whole-body reversible cryopreservation, providing patients with hope for future medical advancements.To realize our ambitious objectives, we are curating a diverse team of experts to innovate perfusion systems, develop cryoprotectant formulations, and engineer cutting-edge vitrification and rewarming technologies. Additionally, we are expanding our medical hibernation team to tackle the complexities of whole-body cryopreservation, starting with rodent models.We envision a future where logistics never hinder the availability of transplantable organs, and where terminal diagnoses can be reconsidered, allowing patients to await the arrival of future medical solutions safely.About the RoleAs a Machine Learning Engineer / Scientist at Until, you will play a pivotal role in our computational team, transforming experimental data into actionable insights that fuel scientific breakthroughs. You will create high-impact machine learning systems to aid in the development of innovative cryoprotectant formulations, engineer biologically-inspired antifreeze proteins, and unravel the physics underlying vitrification and rewarming processes. You will lead projects end-to-end, encompassing data collection design, data pipeline architecture, model training and evaluation, and the deployment of user-friendly tools for our scientific team.

Join Until, a pioneering moonshot company dedicated to revolutionizing biology with our innovative 'pause button' technology. We are focused on advancing organ-scale reversible cryopreservation, a groundbreaking method that preserves donated organs at subzero temperatures without ice formation. This technology allows for the uniform rewarming of organs, making them viable for transplants. By addressing this critical challenge, we are laying the groundwork for medical hibernation, providing patients with a bridge to future cures.As part of our mission, we are assembling a dynamic, interdisciplinary team to develop advanced perfusion systems, cryoprotectant formulations, controlled-rate freezers, and effective vitrification and rewarming protocols for human tissues. Our medical hibernation team is also engaged in tackling whole-body cryopreservation challenges, starting with rodent models.We aspire to a future where no transplantable organ is lost due to logistical issues, and where no terminal diagnosis is irreversible, enabling patients to safely await the arrival of future medical advancements.About the RoleAs a Software Engineer at Until, you will be instrumental in constructing the computational and infrastructure backbone that accelerates our scientific endeavors. You will design and implement robust data pipelines, develop lab automation interfaces, and create scalable cloud-based systems that support our experimental processes. You will take ownership of projects from inception to completion, collaborate with cross-functional teams, and uphold high standards in code development that aligns with our growing team.

Join Until, a pioneering moonshot company, as we revolutionize biology with our innovative approach to organ-scale reversible cryopreservation. Our mission focuses on preserving donated organs at subzero temperatures without ice formation, ensuring they can be uniformly rewarming for transplant. By tackling this monumental challenge, we aim to establish the groundwork for whole-body reversible cryopreservation, providing patients with a pathway to future medical breakthroughs.To realize our vision, we are building a dynamic interdisciplinary team dedicated to creating advanced perfusion systems, cryoprotectant formulations, and cutting-edge vitrification and rewarming hardware.We foresee a future where logistical barriers do not result in the loss of transplantable organs, and terminal diagnoses can be addressed with safe waiting periods for the advent of future cures.About the RoleAs an Integration Engineer at Until, you will collaborate across various teams to deliver next-generation perfusion, cooling, and rewarming systems. You will independently manage the deployment of these systems while working closely with scientists throughout the organization to ensure seamless integration across hardware and software stacks.

Until is an innovative moonshot company on a mission to create a biological 'pause button.' Currently, we are focusing on organ-scale reversible cryopreservation, which involves preserving donated organs at subzero temperatures without the formation of ice. This groundbreaking technology allows us to rewarm the organs uniformly for transplantation. By addressing this monumental challenge, we are paving the way for comprehensive whole-body reversible cryopreservation, offering patients a vital bridge to future medical advancements.To accomplish our ambitious goals, we are building a diverse and interdisciplinary team dedicated to developing advanced perfusion systems, innovative cryoprotectant formulations, and cutting-edge vitrification and rewarming technologies.We envision a future where logistical challenges do not result in the loss of any transplantable organs, and no terminal diagnosis is considered final, as patients can safely await the arrival of future medical solutions.About the RoleAs an engineer on the hibernation team, you will be responsible for designing and developing N-of-1 hardware and software systems aimed at cryopreserving entire organisms. This role demands expertise in mechanical design and fabrication, electrical design and implementation, as well as software architecture and development. Your success in this role will position you as the lead engineer to demonstrate the feasibility of whole-body reversible cryopreservation in rodent models.

Join Altos Labs as a Machine Learning Scientist or Senior Machine Learning Scientist and be at the forefront of innovative research in the virtual cell space. Our team is dedicated to advancing the field of machine learning and its applications in biological research.

Join our innovative team at Lever as a Senior Scientist, where you will play a crucial role in advancing our mission to redefine talent acquisition. Lever is at the forefront of developing cutting-edge hiring software that empowers companies such as Netflix, Shopify, and Spotify to attract and retain top talent. We pride ourselves on fostering a people-first culture, investing in our employees, and being recognized as a premier workplace in San Francisco and across the United States.As a Senior Scientist, you will leverage your expertise to contribute significantly to our projects and help shape the future of hiring technology. Your insights and skills will be invaluable as we continue to scale and innovate.

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 the Arena Intelligence TeamArena Intelligence is a cutting-edge platform dedicated to evaluating the performance of AI models in real-world scenarios. Founded by a team of researchers from UC Berkeley’s SkyLab, our mission is to push the boundaries of AI through comprehensive measurements and advancements.Every month, millions turn to Arena Intelligence to gain insights into the performance of pioneering AI systems. Our community-driven feedback loop helps us create transparent, rigorous, and human-centered evaluations. Major enterprises and AI laboratories trust our assessments for their reliability, alignment, and impact. Our leaderboards have become the benchmark for AI performance, influencing the global discourse on model efficacy and innovation.Our team comprises top researchers, engineers, and builders from prestigious institutions like UC Berkeley, Google, Stanford, DeepMind, and Discord. We prioritize truth, agility, craftsmanship, curiosity, and impactful work over traditional hierarchies, fostering an environment where diverse talents can thrive. Our office is a hub of excellence, energy, and focus.Your Role as a Machine Learning ScientistWe are looking for a skilled Machine Learning Scientist to enhance our methods for evaluating and understanding AI models. You will design and analyze experiments that reveal the factors contributing to the usefulness, trustworthiness, and capabilities of models based on human preference signals. Your contributions will lay the groundwork for scalable AI understanding.This interdisciplinary role involves close collaboration with engineers, product teams, marketing, and the wider research community to develop innovative methodologies for model comparison, preference data analysis, and performance factor disentangling, including style, reasoning, and robustness. Your work will directly impact our public leaderboard and the resources we provide to model developers.If you are intrigued by open-ended challenges, rigorous evaluations, and impactful research, we invite you to apply. We are looking for candidates with:Hands-on experience in training large-scale models, including reward and preference models, as well as fine-tuning LLMs using methodologies such as RLHF, DPO, and contrastive learning.A solid foundation in machine learning and statistics, with proven experience in designing innovative training objectives, evaluation schemes, or statistical frameworks to enhance model reliability and alignment.Proficiency in the entire experimental pipeline, from dataset design and large-batch training to thorough evaluation and ablation, with an understanding of scalability for production.

Join Arcade as a Senior Machine Learning Engineer, where you'll be at the forefront of AI innovation. In this pivotal role, you will leverage advanced machine learning algorithms to create and enhance cutting-edge solutions. Collaborate closely with cross-functional teams to drive impactful projects from ideation to deployment.

Join our innovative team as an Engineer at leverdemo-8! This role is part of our ongoing efforts to enhance Lever's testing environment. Please note, this posting is for testing purposes only and not for actual recruitment.At Lever, we are dedicated to revolutionizing the recruitment and hiring process, providing cutting-edge software solutions to industry leaders like Netflix, Yelp, Cirque du Soleil, Shopify, and Spotify. As we continue to grow, we seek talented individuals who are passionate about transforming talent acquisition. Lever has been recognized as the #1 workplace in San Francisco and a top employer across the United States. Our team, known as 'Leveroos', is our most valuable asset, and we are committed to fostering a people-first culture that prioritizes the well-being and growth of our employees.

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.

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.

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.

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.”

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.

Aquabyte is on the lookout for a Machine Learning Engineer to join our innovative team dedicated to transforming fish farming practices globally. In this role, you will be pivotal in developing and deploying advanced algorithms designed for fish farms worldwide. Your primary focus will be on the software and machine learning model development for our on-camera and cloud-based software solutions.Our MissionAt Aquabyte, we are driven by a bold mission to enhance the sustainability and efficiency of aquaculture. By optimizing fish farming practices, we aim to support the production of healthy, low-carbon protein while addressing one of the major contributors to climate change. As the fastest growing food production sector globally, aquaculture presents an unprecedented opportunity to leverage technology in preserving marine ecosystems for future generations.We pride ourselves on being a diverse and mission-oriented team eager to collaborate with like-minded individuals. If our vision resonates with you, we encourage you to reach out.Our ProductWe currently focus on empowering salmon farmers with the tools needed to understand their fish populations and make environmentally conscious decisions. Utilizing custom underwater cameras, computer vision, and machine learning, we can accurately quantify fish weights, assess health status, and devise optimal feeding strategies in real time. Our solution encompasses on-site hardware for image capture, cloud data processing pipelines, and a user-friendly web application. This multifaceted approach presents numerous exciting challenges across our technology stack.Above all, Aquabyte is committed to customer satisfaction. Our product development is guided by the needs of fish farmers, ensuring that delighting our customers remains at the forefront of our efforts. We are dedicated to building a collaborative, global team.The RoleAs a Machine Learning Engineer, you will be tasked with creating machine learning models and pipelines, as well as managing databases and data infrastructure. Your responsibilities will include conducting comprehensive data analyses and constructing statistical models to infer biological processes. Working within the AI team, you will develop image and video inference pipelines to evaluate the weight, health, and behavior of individual fish and entire populations. Collaboration with experienced engineers from both industry and academia will be a key aspect of your role.

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.

About Scale AI At Scale AI, we are dedicated to propelling the advancement of AI applications. Over the past eight years, we have established ourselves as the premier AI data foundry, supporting groundbreaking innovations in fields such as generative AI, defense technologies, and autonomous vehicles. Following our recent Series F funding round, we are intensifying our efforts to harness frontier data, paving the way toward achieving Artificial General Intelligence (AGI). Our work with enterprise clients and governments has enhanced our model evaluation capabilities, allowing us to expand our offerings for both public and private evaluations. About the ACE Team The Agent Capabilities & Environments (ACE) team, a vital part of Scale’s Research organization, unites customer-focused Researchers and Applied AI Engineers. Our primary mission is to conduct research on agent environments and reinforcement learning reward signals, benchmark autonomous agent performance in real-world contexts, and develop robust data programs aimed at enhancing the capabilities of Large Language Models (LLMs). We are committed to creating foundational tools and frameworks for evaluating models as agents, focusing on autonomous agents that interact dynamically with a wide range of external environments, including code repositories and GUI interfaces. About This Role This position sits at the cutting edge of AI research and its practical applications, concentrating on the data types necessary for the development of state-of-the-art agents, including browser and software engineering agents. The ideal candidate will investigate the data landscape required to propel intelligent and adaptable AI agents, steering the data strategy at Scale to foster innovation. This role demands not only expertise in LLM agents and planning algorithms but also creative problem-solving skills to tackle novel challenges pertaining to data, interaction, and evaluation. You will contribute to influential research publications on agents, collaborate with customer researchers, and partner with the engineering team to transform these advancements into scalable real-world solutions.

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!