Research Scientist - World-action Foundation Model, Robotics

Applied Intuition

Sunnyvale, California, United States
Base: $126,000 - $423,000 usd annually; bonus/equi...
On-site
Strong research record in 3d vision and reconstruction
Msc or phd in machine learning and computer vision
Technical experience in python, pytorch, and distributed ml training
Applied Intuition is seeking multiple Research Scientists to contribute to cutting-edge technology in the field of physical AI, specifically focusing on autonomous driving and robotics. The ideal candidates will have a strong research background in 3D vision and machine learning, and will work closely with cross-functional teams to advance their innovative solutions

Job Summary

  • The mission of the group is to create cutting-edge technology enabling next-generation physical AI with emphasis on end-to-end autonomous driving and robotic generalist.
  • Researchers will conduct research on pretraining world-action foundation models serving purposes for both robot action and simulation world generation.
  • Compensation includes base salary ranging from $126,000 to $423,000 USD annually, along with equity, comprehensive health benefits, and a 401k match.

Matching Summary

Match Score: 85

Applied Intuition is seeking multiple Research Scientists to contribute to cutting-edge technology in the field of physical AI, specifically focusing on autonomous driving and robotics. The ideal candidates will have a strong research background in 3D vision and machine learning, and will work closely with cross-functional teams to advance their innovative solutions.

Salary

Base: $126,000 - $423,000 USD annually; Bonus/Equity: Equity in form of options and/or restricted stock units; Benefits: Comprehensive health, dental, vision, life, disability insurance, 401k match, learning stipends

Skills & Requirements

Must-have

  • Strong research record in 3D vision and reconstruction
  • MSc or PhD in machine learning and computer vision
  • Technical experience in Python, Pytorch, and distributed ML training

Nice-to-have

  • Hands-on experience with feed-forward Gaussian splatting
  • Experience with multi-modal foundation model pretraining
  • Background in human data processing and incorporation

Key Requirements

  • MSc or PhD in machine learning or computer vision
  • Publications in top-tier conferences or journals
  • Experience with autonomy and robotics applications

Work Rights

Not specified

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