Tech Stack
Responsibilities
- 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).
- Lead cross-team technical decisions on training frameworks, data pipelines, and model evaluation infrastructure.
Soft Skills
Machine LearningAI ResearchTechnical Decision-MakingRoboticsEmbodied AI
Benefits
- Health Insurance
Culture
Impact-OrientedInnovationCross-Functional CollaborationExperimental Mindset
Requirements
Required: MS or Ph.D. in Computer Science, Machine Learning, Robotics, Physics, or a related field, or equivalent experience
Regions: Us
Get jobs like this in your inbox
Weekly Representation Learning, World Models, Policy Optimization hiring trends and salary data — free.
Join 6 engineers getting weekly insights
Get market intelligence in your inbox
Free weekly insights on tech hiring trends, salaries, and in-demand stacks.
Already a subscriber? Sign in
About Snowflake
Industry: data warehousing
Size: enterprise
Snowflake is a data warehousing company powering the era of the agentic enterprise and empowering enterprises to achieve their full potential through impact, innovation, and collaboration.
View company profile →