Senior Deep Reinforcement Learning Engineer - Autonomous Driving
$224k - $357k • US, CA, Santa Clara
Posted 1mo ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
On-site
Categories
AI Research Engineer
About the job
NVIDIA is seeking a Reinforcement Learning Engineer to join its mission in building intelligent, safe, and efficient self-driving technology. This role involves pushing the boundaries of autonomous vehicle decision-making and planning by leveraging Deep Reinforcement Learning (RL). As a world leader in AI and high-performance computing, NVIDIA offers a unique platform where innovative research meets real-world production, aiming to redefine transportation globally.
Responsibilities
- Build and implement new Reinforcement Learning (RL) algorithms for autonomous vehicle decision-making and planning.
- Develop and maintain scalable training pipelines and simulation environments for RL training.
- Collaborate with perception and planning teams to integrate RL models into the autonomous driving stack.
- Benchmark RL model performance against imitation learning baselines in complex urban environments.
- Optimize and deploy RL models to production-grade automotive hardware.
Requirements
- BS or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or equivalent experience).
- 12+ years of experience in the related field.
- Solid background in Reinforcement Learning, including policy gradient methods (PPO, GRPO), actor-critic architectures, on-policy and off-policy RL.
- Proficiency in PyTorch or TensorFlow and real experience with RL-related algorithms.
- Experience in C++ and Python development for real-time systems.
- Strong analytical and problem-solving skills, with a track record of implementing and debugging complex RL systems.
Benefits
- Equity
- Benefits