Staff Research Scientist (AI)

TL;DR

Staff Research Scientist (AI): Building the next-generation training and learning platform for physical AI with an accent on representation learning, world models, and policy optimization. Focus on architecting scalable training infrastructure, developing latent world models, and translating research prototypes into production-grade systems.

Location: Must be based in Bellevue, WA, USA

Compensation: $236,000 – $339,200

Company

Snowflake is a cloud-based data platform company focused on empowering enterprises through data-driven innovation and agentic AI systems.

What you will do

• Design and build scalable training infrastructure for representation models like CLIP, DINO, and I-JEPA.
• Develop latent world models that learn environment dynamics through imagined rollouts.
• Architect and implement vision-language-action models and diffusion-based policy pipelines.
• Build generative simulator frameworks for controllable, physically plausible future states.
• Lead cross-team technical decisions regarding training frameworks, data pipelines, and model evaluation.
• Drive research-to-production pathways to translate prototypes into reliable platform capabilities.

Requirements

• 8+ years of experience in machine learning engineering or AI research.
• Deep expertise in at least two areas: representation learning, world models, reinforcement learning, generative modeling, or robotics.
• Hands-on experience training large-scale models with distributed compute.
• Strong software engineering fundamentals including system design and performance optimization.
• Demonstrated ability to drive cross-team technical initiatives with ambiguity.
• MS or Ph.D. in Computer Science, Machine Learning, Robotics, Physics, or equivalent experience.

Nice to have

• Experience with latent dynamics modeling or physics-informed neural networks.
• Contributions to open-source ML frameworks or foundation model training codebases.
• Background in scientific modeling such as molecular, materials, or climate science.
• Publications at top venues like NeurIPS, ICML, ICLR, CVPR, CoRL, or RSS.

Culture & Benefits

• Opportunity to define a new research direction from the ground up with high autonomy.
• Access to massive data scale and infrastructure resources of a platform company.
• Collaborative environment focused on shipping frontier models and production agentic systems.
• Culture that prioritizes impact, innovation, and rapid experimentation.