Machine Learning Research Scientist

At Scale AI, we are at the forefront of artificial intelligence, driving innovation through our advanced data, infrastructure, and tooling that empower the most sophisticated models worldwide. Our teams thrive at the intersection of pioneering research, extensive engineering, and practical deployment, collaborating with leading labs, enterprises, and government entities to explore the vast potential of Generative AI. As AI technology evolves from static models to dynamic, intelligent systems, Scale AI is dedicated to establishing the essential research foundations, evaluation methodologies, and reinforcement learning infrastructure that will shape this transformative era. Join our high-impact research organization, where you will contribute to advancing large language models, post-training evaluation, and agent-based reinforcement learning environments, influencing the future of AI development and implementation. As the Research Scientist Manager, you will spearhead a distinguished team of research scientists and engineers, define the strategic research roadmap, and oversee projects from initial prototyping to final deployment. You will excel in a fast-paced environment, harmonizing deep technical leadership with effective people management, visionary goal setting, and successful delivery.

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.

At Scale AI, we collaborate with leading AI laboratories to supply high-quality data and foster advancements in Generative AI research. We seek innovative Research Scientists and Research Engineers with a strong focus on post-training techniques for Large Language Models (LLMs), including Supervised Fine-Tuning (SFT), Reinforcement Learning from Human Feedback (RLHF), and reward modeling. This position emphasizes optimizing data curation and evaluation processes to boost LLM performance across text and multimodal formats. In this pivotal role, you will pioneer new methods to enhance the alignment and generalization of extensive generative models. You will work closely with fellow researchers and engineers to establish best practices in data-driven AI development. Additionally, you will collaborate with top foundation model labs, providing critical technical and strategic insights for the evolution of next-generation generative AI models.

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.

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.

Become a Pioneer in Sleep FitnessAt Eight Sleep, we're dedicated to unlocking human potential through optimal sleep. As the world's first sleep fitness company, we are revolutionizing what it means to be well-rested by creating the most advanced hardware, software, and AI technology. Our innovative products enhance mental, physical, and emotional performance by transforming each night into a personalized, data-driven recovery journey. Trusted by high achievers, professional athletes, and health-conscious individuals across over 30 countries, we have been recognized by Fast Company as one of the Most Innovative Companies in 2019, 2022, and 2023, and honored twice by TIME's “Best Inventions of the Year.” Our high-performance team operates with speed, focus, and a commitment to impact. We don't just create; we refine and obsess over every detail to ensure our members sleep better and wake up stronger.Every position at Eight Sleep offers the opportunity to innovate cutting-edge technology, collaborate with exceptional talent, and contribute to a future where sleep is a powerful tool for well-being. If you're ready to break away from the ordinary and eager to build at the forefront of possibility, this is your chance to join us in reshaping how the world sleeps and what we can achieve upon waking.Our Culture: High Standards, No CompromiseOur mission demands intensity, and at Eight Sleep, we embody the mindset of the world's top performers: focused, relentless, and committed to being in the top 1% of our field. Inspired by the relentless drive of legends like Kobe Bryant, we apply that mentality to bold ideas, next-gen technology, and impeccable execution. This is not a standard 9-to-5 role; our team is dedicated, often working 60+ hours per week—not out of obligation, but out of passion. If you thrive under pressure and seek to do the most meaningful work of your career, you'll find a home here. If you prefer an easier path, this position is not for you.Your RoleAs a Machine Learning Research Scientist at Eight Sleep, you will be at the cutting edge of sleep innovation. Your mission will be to leverage innovative technology, minimalistic design, and proven clinical science to personalize and enhance sleep experiences, fundamentally changing how people sleep for the better.Our revolutionary temperature-regulated technology, the Pod, has been recognized as a game changer, enhancing health and happiness by transforming sleep. Join us in making sleep count for more.

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.

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.

Join Our Team at Rad AIAt Rad AI, we are dedicated to transforming the healthcare landscape through the power of artificial intelligence. Established by a radiologist, our innovative AI solutions are revolutionizing the field of radiology, enhancing patient care, alleviating clinician burnout, and significantly reducing the time required for report generation. With access to one of the largest proprietary datasets of radiology reports globally, our AI technologies have facilitated the discovery of numerous new cancer diagnoses and halved error rates across tens of millions of reports.Having raised over $140 million in funding, including a highly successful Series C round of $68 million led by Transformation Capital, we are now valued at $528 million. Our prestigious investors, such as Khosla Ventures, World Innovation Lab, Gradient Ventures, and Cone Health Ventures, are all committed to supporting our mission to empower healthcare professionals with cutting-edge AI tools.Our latest breakthroughs in generative AI are utilized by thousands of radiologists every day, supporting nearly half of all medical imaging across the United States, in partnership with esteemed healthcare organizations like Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked as the 19th fastest-growing company in North America by Deloitte, we are committed to creating AI-powered solutions that make a real difference. Recently, Rad AI was also featured on CNBC’s Disruptor 50 list, showcasing the innovation and momentum behind our mission.If you are eager to impact the future of healthcare positively, we would be thrilled to have you join our talented team!Why You Should Join UsWe are seeking a Staff Machine Learning Research Scientist to define and lead Rad AI's next wave of applied research in Natural Language Processing (NLP) and clinical AI. You will engage with large language models, retrieval systems, representation learning, speech processing, and multimodal modeling, prioritizing evaluation and reliability alongside achieving state-of-the-art outcomes. This role offers you the chance to take ownership of projects and establish a direct pathway from research to product implementation.As part of our team, you will work closely with clinicians, engineers, and product leaders to translate foundational research into practical applications that enhance healthcare delivery.

AI Research ScientistOverviewJoin Physical Superintelligence, an innovative startup rooted in prestigious institutions such as Harvard, MIT, Johns Hopkins, Oxford, the Institute for Advanced Study, and the Perimeter Institute. We are at the forefront of building AI systems designed to uncover groundbreaking insights in physics on a grand scale. We are in search of talented AI researchers dedicated to developing reinforcement learning agents and training frameworks that propel scientific discovery.Key Responsibilities- Develop and optimize AI systems aimed at physics discovery, collaborating with physicists on verification harnesses and engineers on training infrastructure.- Address critical AI research questions related to agent learning in physics reasoning, action space design for scientific exploration, reward structure development, and scalable training systems.- Construct and train reinforcement learning agents leveraging cutting-edge methodologies such as PPO, SAC, MuZero, and multi-agent self-play.- Design agent architectures tailored for physics reasoning and scientific tool utilization.- Execute training curricula and reward structures for discovery tasks.- Establish evaluation workflows and benchmarks to assess physics reasoning capabilities.- Develop instrumentation to analyze agent behavior and learning dynamics.- Collaborate closely with physicists and engineers to refine system design and architecture.Candidate ProfileWe are looking for candidates with a strong background in developing agents and training models using reinforcement learning. Proficiency in modern machine learning frameworks and experience with distributed training systems is essential, alongside a proven track record of deploying effective AI systems.Essential Skills:- Practical experience with contemporary reinforcement learning algorithms including PPO, SAC, MuZero, and multi-agent self-play.- Proficient in PyTorch or JAX, with hands-on experience in distributed training using Ray, XLA, or Accelerate, and familiarity with modern pretraining workflows.Preferred Background:- A strong foundation in physics or mathematics that enhances intuition for physical reasoning and mathematical modeling.- Experience applying agents in simulators, games, scientific tool use, or benchmark design employing rigorous experimental methodologies.

About Retell AI Retell AI develops advanced voice AI technology for call centers, using first-principles approaches to create intelligent voice agents. These agents help businesses manage sales, support, and logistics communications while reducing reliance on large human teams. The company has reached $36M ARR in just 18 months, backed by Y Combinator and Alt Capital. With a team of 20, Retell AI is building a comprehensive customer experience platform, aiming for AI-powered contact centers by 2026. The vision: intelligent agents that execute, monitor, and improve customer interactions with minimal human oversight. Named a top 50 AI app by a16z: https://tinyurl.com/5853dt2x Ranked #4 on Brex's Fast-Growing Software Vendors of 2025: https://www.brex.com/journal/brex-benchmark-december-2025 Featured among top startups: https://leanaileaderboard.com/ Role Overview: Research Scientist - Voice AI Innovation This role centers on advancing machine learning for human-like voice agents in real-world settings. The Research Scientist will explore new methods in large language models (LLMs) and audio models, design evaluation techniques, and prototype systems that improve reasoning, reduce latency, and enhance conversational quality. The work involves open-ended ML challenges, rapid experimentation, and direct influence on the performance and cognitive abilities of voice AI systems at scale. Location San Francisco Bay Area

AI Research ScientistAt Substrate, we are tackling a critical technological challenge that impacts the United States. Positioned at the crossroads of advanced manufacturing and innovative physics, our mission is to develop transformative technologies that will revolutionize the semiconductor industry and bolster America's technological dominance. Our team comprises top-tier scientists, engineers, and technical specialists dedicated to pushing the boundaries of technology for the benefit of the nation.As an AI Research Scientist, you will play a key role in enhancing and accelerating research and development processes by harnessing machine learning techniques for scientific simulations and modeling. You will also focus on establishing internal AI capabilities throughout our organization. This position merges cutting-edge physics with artificial intelligence, requiring hands-on development of AI-enhanced tools that facilitate groundbreaking research. You will also contribute to building the infrastructure and expertise required for our technical teams to effectively use AI in their workflows. Whether you are a physicist who has adopted machine learning or an AI expert with a solid scientific background, you will be instrumental in shaping our approach to utilizing AI to expedite our internal R&D efforts.

As a premier data and evaluation partner for cutting-edge AI firms, Scale AI is committed to enhancing the evaluation and benchmarking of large language models (LLMs). We are developing industry-leading LLM evaluations that set new benchmarks for model performance assessment. Our mission is to create rigorous, scalable, and equitable evaluation methodologies that propel the next evolution of AI capabilities.Our Research teams collaborate with top AI laboratories to provide high-quality data and expedite advancements in Generative AI research. As the Tech Lead/Manager of the LLM Evaluations Research team, you will guide a skilled team of research scientists and engineers dedicated to crafting and applying innovative evaluation methodologies, metrics, and benchmarks that assess the strengths and weaknesses of our advanced LLMs. This pivotal role involves designing and executing a strategic roadmap that establishes best practices in data-driven AI development, thus accelerating the development of the next generation of generative AI models in collaboration with leading foundational model labs.

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.

About Retell AI Retell AI builds voice AI technology that helps businesses transform their call center operations. In just 18 months, thousands of companies have adopted Retell’s AI voice agents to streamline sales, support, and logistics, work that once required large human teams. Backed by investors including Y Combinator and Alt Capital, Retell has grown annual recurring revenue from $5M to $36M with a focused team of 20. The company’s goal for 2026: a modern customer experience platform where AI powers entire contact centers. Retell is developing AI “workers” that can serve as frontline agents, quality assurance analysts, and managers, handling, evaluating, and improving customer interactions on their own. Named a top 50 AI app by a16z: https://tinyurl.com/5853dt2x Ranked #4 on Brex’s Fast-Growing Software Vendors of 2025: https://www.brex.com/journal/brex-benchmark-december-2025 Featured on the Lean AI Leaderboard: https://leanaileaderboard.com/ Role Overview: Research Scientist – LLM Retell AI is hiring a Research Scientist focused on large language models (LLMs) and audio processing. This role suits machine learning researchers who want to push the boundaries of real-time AI and see their work in production. What You Will Do Investigate new approaches in large language models and audio processing for human-like voice agents Design and implement evaluation methods for complex, real-world conversational systems Prototype systems to improve reasoning, reduce latency, and enhance conversation quality Work closely with engineering and product teams to bring research advances into production Impact Research at Retell directly shapes the capabilities of voice AI agents for thousands of businesses. The work blends advanced research with practical deployment, improving how customers interact with automated systems across industries. Location This position is based in the San Francisco Bay Area.

Artificial Intelligence (AI) is becoming increasingly crucial across all sectors of society. At Scale AI, our mission is to expedite the advancement of AI applications. With nine years of experience, we have established ourselves as the leading AI data foundry, facilitating groundbreaking developments in AI, including generative AI, defense applications, and autonomous vehicles. Following our recent investment from Meta, we are committed to enhancing our capabilities by developing cutting-edge post-training algorithms that are essential for optimizing complex agents in enterprises globally.The Enterprise ML Research Lab is at the forefront of this AI revolution. We are dedicated to crafting a suite of proprietary research tools and resources that cater to all of our enterprise clients. As a Machine Learning Research Engineer focusing on Agents, you will apply our Agent Reinforcement Learning (RL) training and building algorithms to real-world enterprise datasets across our clients and benchmarks. Your role will involve developing top-tier Agents that achieve state-of-the-art results through a blend of post-training and agent-building algorithms.If you are passionate about influencing the trajectory of the modern Generative AI movement, we would love to hear from you!

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.

At Merge Labs, we are at the forefront of research, dedicated to uniting biological and artificial intelligence to enhance human capability, autonomy, and overall experience. Our innovative approach focuses on developing revolutionary brain-computer interfaces that offer high-bandwidth interaction with the brain, seamlessly integrate advanced AI, and are designed to be safe and accessible for everyone.About the Team:Our Bio team is responsible for designing, constructing, and characterizing the biotechnologies that underpin the next generation of brain-computer interfaces. By integrating molecular engineering, synthetic biology, neuroscience, and cutting-edge physical methods such as ultrasound, we aim to establish less invasive, high-bandwidth connections with neurons. The Bio team is dedicated to developing our core molecular technologies, validating their performance both in vitro and in vivo, and showcasing their advanced capabilities in animal models. We create custom experimental setups and pipelines while collaborating closely with engineers and data scientists to tackle some of the most challenging problems in biotechnology.About the Role:We are seeking a Senior/Principal Machine Learning Biophysicist to spearhead the creation of scalable molecular dynamics pipelines, integrating physics-based models with machine learning frameworks. You will build the molecular modeling foundations of the company from first principles, establishing tools and workflows for simulating, analyzing, and interpreting biomolecular dynamics to elucidate function relationships. Over time, your contributions will help translate these frameworks into predictive models that expedite molecular engineering, guide experimental campaigns, and facilitate the discovery of highly functional molecules.Key Responsibilities:Develop the scientific and engineering framework for protein structure modeling and molecular dynamics, along with integrations into downstream ML frameworks.Collaborate with wet-lab scientists to establish realistic optimization objectives and encode domain-specific priors and constraints.Prototype modeling frameworks utilizing internal and public datasets; benchmark and validate performance.Make complex analyses accessible to non-domain experts through democratization of first-principles analysis.Lead the development of ML frameworks that explicitly incorporate first-principles priors.Stay abreast of the latest advancements in deep learning and molecular dynamics.