ML Engineer, Behavior Planning — Autonomy in Motion

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

Benefits offered by this job

Annual bonus

Equity compensation

Benefits

Job summary

Aurora is seeking an ML Engineer to join the Behavior Planning Team. You will define architecture for onboard planning models, develop offboard critics, and build a simulation engine with world models to test the Aurora Driver.

You will bridge research and production by deploying models on real vehicles that must meet high safety standards. This role emphasizes advancing state-of-the-art autonomous driving tech, working with large-scale models and distributed computing, and collaborating across

Qualifications

• BS, MS, or PhD in Robotics, ML, CS or related quantitative field, or equivalent practical experience.
• 2+ years of experience developing state-of-the-art ML models, research or production.
• Hands-on experience with Imitation Learning or RL for physical or simulated agents.
• Experience training large models on massive datasets using distributed computing.
• Fluency in Python with high-performance, maintainable code.
• Deep experience with PyTorch and modern ML architectures (Transformers, Diffusion Models).

Responsibilities

• Define onboard planning model architecture and deploy large-scale models trained with IL and RL.
• Develop offboard critic models to evaluate driving behavior at scale.
• Architect offboard foundation models powering a realistic world model simulation engine.
• Bridge research and production by deploying models on production vehicles.

Skills

Python

Imitation Learning

Reinforcement Learning

Distributed computing

Transformers

Diffusion Models

Education

Robotics/ML/CS degree

Tools

PyTorch

C++

Job description

Aurora is seeking an ML Engineer to join the Behavior Planning Team. You will define architecture for onboard planning models, develop offboard critics, and build a simulation engine with world models to test the Aurora Driver.

You will bridge research and production by deploying models on real vehicles that must meet high safety standards. This role emphasizes advancing state-of-the-art autonomous driving tech, working with large-scale models and distributed computing, and collaborating across