ML Engineer - Autonomous Driving Behavior Planning

Aurora; Mountain View (CA); Hybrid; USD 139,000 - 223,000; Full time

Benefits offered by this job

Annual bonus

Equity compensation

Benefits

Job summary

Aurora seeks a Machine Learning Engineer to join the Behavior Planning Team, working on onboard planning models, offboard critics, and a simulator to test the Aurora Driver. You will bridge research advances with deployments on production vehicles, ensuring safety and performance on public roads.

You will apply ML methods including imitation and reinforcement learning, training large models with distributed computing, and leveraging PyTorch and Transformers in a high-impact role.

Qualifications

• 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, either in a research or production setting.
• Hands-on experience working on Imitation Learning or Reinforcement Learning applied to physical or simulated agents.
• Experience training large models on massive datasets using distributed computing.
• Fluency in Python, with a focus on writing high-performance, maintainable code.
• Deep experience with PyTorch (preferred) or another modern ML framework, and a mastery of modern ML architectures including Transformers and Diffusion Models.

Responsibilities

• Define the architecture of our onboard planning models: Develop and deploy large-scale models trained with Imitation Learning and Reinforcement Learning that enable the Aurora Driver to navigate complex environments with human-like fluidity and superhuman safety.
• Revolutionize evaluation: Develop powerful offboard critic models that can evaluate driving behavior at scale, identifying subtle nuances in comfort, progress, and safety that traditional heuristics miss.
• Build our next-generation simulation engine: Architect cutting-edge offboard foundation models that power our simulation engine, creating realistic world models to test the Aurora Driver against an infinite variety of edge cases.
• Bridge research and production: Reach new frontiers of autonomous driving technology by pushing forward the state-of-the-art, but also deploy your models on real production vehicles that drive on public roads and must meet the highest standards of safety.

Skills

Python

PyTorch

Transformers

Diffusion Models

Imitation Learning

Reinforcement Learning

Distributed computing

Education

BS, MS, or PhD in Robotics, Machine Learning, Computer Science

Tools

C++

Job description

Aurora seeks a Machine Learning Engineer to join the Behavior Planning Team, working on onboard planning models, offboard critics, and a simulator to test the Aurora Driver. You will bridge research advances with deployments on production vehicles, ensuring safety and performance on public roads.

You will apply ML methods including imitation and reinforcement learning, training large models with distributed computing, and leveraging PyTorch and Transformers in a high-impact role.