Lead 4–6 Physical AI researchers; contribute hands-on coding (~60%).
Develop and evaluate large-scale Foundation Models (VLAs, World models) for robotics.
Hands-on modeling: implement, train and test SOTA architectures.
Data strategy: design robotic-native pipelines with automated trajectory annotation.
Collaborate with customers and cross-functional teams to deploy research.

🎯 Requirements

Deep Learning mastery: PyTorch, Transformers, self-supervised learning.
VLM/VLA experience: CLIP, PaLM-E; spatial reasoning for embodied tasks.
Generative AI: diffusion models and generative world models.
Physical AI & software: embodied AI, RL and multi-modal sensor fusion.
Infrastructure & leadership: distributed GPU training; 1+ year leading teams.

🎁 Benefits

Comprehensive health, dental and vision coverage.
Retirement benefits.
Learning and development stipend.
Generous PTO.
Equity-based compensation; commuter stipend.

Apply on employer's website

This employer gathers applications via their own applicant tracking system.

You will be redirected to an external application form.

Share job

Meet JobCopilot: Your Personal AI Job Hunter

Automatically Apply to Engineering Jobs. Just set your preferences and Job Copilot will do the rest — finding, filtering, and applying while you focus on what matters.

Activate JobCopilot