Job Overview
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 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 cr