Staff Research Scientist

Who you are

• 8+ years of relevant experience in machine learning engineering, AI research, or a closely related field (or equivalent experience)
• Deep expertise in at least two of the following: representation learning, world models, reinforcement learning, generative modeling, robotics/embodied AI, or scientific ML
• Hands-on experience training large-scale models (vision, language, or multimodal) with distributed compute
• Strong software engineering fundamentals: system design, performance optimization, and production-quality code
• Demonstrated ability to drive cross-team technical initiatives with ambiguity and limited direction
• Track record of translating research ideas into working systems at scale
• MS or Ph.D. in Computer Science, Machine Learning, Robotics, Physics, or a related field, or equivalent experience
• Experience with latent dynamics modeling, model-based RL, or physics-informed neural networks (GraphCast, FourCastNet, AlphaFold-style architectures)
• Contributions to open-source ML frameworks or foundation model training codebases
• Background in scientific/structured models (molecular modeling, materials science, weather/climate)
• Experience building controllable video generation or neural simulation environments
• Publications at top venues (NeurIPS, ICML, ICLR, CVPR, CoRL, RSS)
• We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake

What the job involves

• We are hiring a Staff Research Scientist, Physical AI for our AI Research team
• You will build the next-generation training and learning platform for physical AI: models that perceive, reason about, and act within structured environments
• This is a greenfield (0 to 1) effort at the intersection of representation learning, world models, and policy optimization. You will help define its technical direction from day one
• Design and build scalable training infrastructure for representation models (e.g., contrastive and self-supervised approaches like CLIP/SigLIP, DINO/MAE, and joint-embedding predictive architectures)
• Develop latent world models that learn environment dynamics through imagined rollouts, enabling model-based reasoning and planning (Dreamer-style, I-JEPA/V-JEPA families)
• Architect and implement action/policy model pipelines, including vision-language-action models and diffusion-based policy learning
• Build generative simulator frameworks that produce controllable, physically plausible future states (video world models in the spirit of Cosmos/Genie/Sora)
• Develop multimodal generative model capabilities that fuse visual, language, and structured inputs for downstream reasoning and decision-making
• Lead cross-team technical decisions on training frameworks, data pipelines, and model evaluation infrastructure
• Drive research-to-production pathways, translating prototype systems into reliable, performant platform capabilities
• Contribute to the broader research community through publications, open-source releases, and collaboration with academic partners
• This is a rare opportunity to define a new research direction from the ground up
• You won't be maintaining existing systems or iterating on someone else's roadmap
• You'll be building the foundational training platform for physical AI at a company with the infrastructure, data scale, and research ambition to make it real
• Our team already ships frontier models (Arctic LLM, Arctic Inference) and production agentic systems (Snowflake Intelligence)
• You'll have the resources of a platform company with the pace and autonomy of a research lab
• Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth

Benefits

• Comprehensive health insurance plans
• Health savings accounts
• Robust retirement plans
• Life and disability insurance
• Weekly online lunch and learns
• Virtual workout classes
• Ergonomic work-from-home equipment
• On-demand mental health and wellness programs
• Fertility benefits and family planning resources
• Generous time-off and various leave plans
• Onsite and Remote Work
• Employee discounts and pre-tax selections
• New hire equity + Employee Stock Purchase Plan (ESPP)
• Quarterly bonus or commission program