Snowflake에서 물리 AI(Physical AI)를 위한 차세대 학습 플랫폼을 구축할 Staff Research Scientist를 채용합니다. 표현 학습(Representation Learning), 월드 모델, 강화 학습 분야의 깊은 전문성을 갖춘 분을 찾습니다. 대규모 모델 학습 경험과 연구를 프로덕션으로 전환할 수 있는 역량이 필수입니다. 연구실 수준의 자율성과 플랫폼 기업의 인프라를 결합한 환경에서 새로운 연구 방향을 주도할 기회입니다.
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, Exotic 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 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
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)
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. 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.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
