ML Engineer, Behavior Planning

What you'll do

• Design and deploy onboard planning models trained with Imitation Learning and Reinforcement Learning; develop offboard critic models to evaluate driving behavior.
• Build foundation models and world models for the simulation engine to test autonomous driving in varied edge cases.
• Advance autonomous-driving research and deploy models on production vehicles operating on public roads.

What they ask for

• BS, MS, or PhD in Robotics, Machine Learning, Computer Science, or a related quantitative field, or equivalent practical experience.
• 2+ years of experience developing state-of-the-art ML models in research or production.
• Hands-on experience with Imitation Learning or Reinforcement Learning applied to physical or simulated agents, and experience training large models on massive datasets using distributed computing.
• Fluency in Python; deep experience with PyTorch (preferred) or another modern ML framework; mastery of Transformers and Diffusion Models.

Nice to have

• Publications in top-tier ML conferences, production deployment experience, or experience developing generative models or neural simulators.
• Fluency in C++.

Pay

$139,000 - $223,000 USD per Year (base salary)

Tools

Python, PyTorch, Transformers, Diffusion Models, C++

AI focus

Develop ML models for autonomous-vehicle planning, driving-behavior evaluation, and simulation, using imitation learning, reinforcement learning, foundation models, and world models.