Staff Research Scientist

Responsibilities

• Design and build scalable training infrastructure for representation models (e.g., CLIP, SigLIP, DINO, MAE)
• Develop latent world models that learn environment dynamics through imagined rollouts
• Architect and implement action/policy model pipelines, including vision-language-action models
• Build generative simulator frameworks that produce controllable, physically plausible future states
• Develop multimodal generative model capabilities fusing visual, language, and structured inputs
• Lead cross-team technical decisions on training frameworks, data pipelines, and evaluation infrastructure
• Drive research-to-production pathways for prototype systems
• Contribute to the research community through publications and open-source releases

Requirements

• 8+ years of experience in machine learning engineering or AI research
• Deep expertise in at least two: representation learning, world models, reinforcement learning, generative modeling, robotics/embodied AI, or scientific ML
• Hands-on experience training large-scale multimodal models with distributed compute
• Strong software engineering fundamentals including system design and performance optimization
• Proven ability to drive technical initiatives in ambiguous environments
• MS or Ph.D. in Computer Science, Machine Learning, Robotics, Physics, or a related field

Preferred Qualifications

• Experience with latent dynamics modeling, model-based RL, or physics-informed neural networks
• Contributions to open-source ML frameworks or foundation model 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 such as NeurIPS, ICML, ICLR, CVPR, CoRL, or RSS

About the Company

Snowflake is powering the era of the agentic enterprise, building foundational training platforms for physical AI and shipping frontier models like Arctic LLM.