Machine Learning Engineering TL, Behavior Planning

About the role

The ML Engineering TL will define the architecture of our onboard planning models, develop and deploy large-scale models trained with Imitation Learning and Reinforcement Learning, architect cutting-edge offboard foundation models, and develop powerful offboard critic models. They will also mentor and lead a team to push the state-of-the-art in ML-based planning.

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
• Build our next-generation simulation engine
• Revolutionize evaluation by developing powerful offboard critic models that can evaluate driving behavior at scale
• Bridge research and production by reaching new frontiers of autonomous driving technology and deploying models on real production vehicles
• Mentor and lead a team to execute highly technical projects

Requirements

• MS or PhD in Robotics, Machine Learning, Computer Science, or a related quantitative field, or equivalent practical experience
• 8 + 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

Qualifications

• A track record of publications in top-tier ML conferences (NeurIPS, ICML, CoRL, CVPR, AAAI)
• Experience deploying complex ML systems in production environments
• Experience in developing generative models or neural simulators for synthetic data generation
• Experience leading small or large teams to execute highly technical projects

Skills

• Strong problem-solving and analytical skills
• Excellent communication and leadership abilities
• Ability to work independently and as part of a team
• Experience with distributed computing and large-scale model training
• Knowledge of Imitation Learning and Reinforcement Learning
• Experience with PyTorch or similar frameworks

Benefits

At Aurora, you will have the opportunity to work on groundbreaking technology that could change the world. You will be part of a dynamic and innovative team, and you will be rewarded with a competitive salary and benefits package.

Pay

The base salary range for this position is $171K - $247K per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions.

Schedule

We operate in a hybrid work environment where Aurorans are in office at least 3 days per week.