Research Scientist - Physical AI​/Multimodality

Position: Staff Research Scientist - Physical AI / Multimodality
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact.

We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.

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.

AS A STAFF RESEARCH SCIENTIST YOU WILL:

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 OUR IDEAL STAFF RESEARCH SCIENTIST, EXOTIC AI WILL HAVE: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 MLHands-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 scaleMS or Ph.D. in Computer Science, Machine Learning, Robotics, Physics, or a related field, or equivalent experience BONUS POINTS FOR THE FOLLOWING:

Experience with latent dynamics modeling, model-based RL, or physics-informed neural networks (Graph Cast, Four Cast Net , Alpha Fold-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)
WHY JOIN OUR AI RESEARCH TEAM AT SNOWFLAKE?

This is a rare…