Senior Deep Reinforcement Learning Engineer - Autonomous Driving

What you'll do

• Build RL algorithms for autonomous-vehicle decision-making and planning; develop scalable training pipelines and simulation environments.
• Integrate RL models with perception and planning teams, and benchmark against imitation-learning baselines in urban environments.
• Optimize and deploy RL models to production-grade automotive hardware.

What they ask for

• BS or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or equivalent experience).
• 12+ years of experience in the related field.
• Strong reinforcement learning background, including policy gradient methods (PPO, GRPO), actor-critic architectures, and on-policy and off-policy RL; experience with RL algorithms using PyTorch or TensorFlow.
• C++ and Python development experience for real-time systems.

Nice to have

• Background shipping autonomous-driving features or working in embodied AI.
• Experience with generative models for policy representation or trajectory modeling, rollout-distribution training, compounding-error mitigation, or large-scale data flywheels.

Pay

224,000 USD - 356,500 USD (base salary)

Tools

PPO, GRPO, PyTorch, TensorFlow, C++, Python

AI focus

Develop, train, benchmark, integrate, optimize, and deploy deep reinforcement learning models for autonomous-vehicle decision-making and planning.