NVIDIA is seeking a Reinforcement Learning Engineer to advance self-driving vehicle technology through innovative research and real-world applications. The role involves building and implementing new RL algorithms for autonomous decision-making and planning. The engineer will collaborate with various teams to integrate RL models into the autonomous driving stack and optimize them for production-grade hardware. This position offers a unique opportunity to contribute to the future of transportation on a global scale.

• BS or higher in Computer Science, Robotics, Electrical Engineering, or a related field.
• 12+ years of experience in the related field.
• Solid background in Reinforcement Learning, including policy gradient methods and actor-critic architectures.
• Proficiency in PyTorch or TensorFlow with real experience in 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 complex RL systems.

• Build and implement brand new Reinforcement Learning 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 unified 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.

• Employees at NVIDIA are often offered comprehensive, day-one benefits—including medical, dental, and vision coverage with HSA support, life and disability insurance, an Employee Assistance Program, and a 401(k) with auto-enrollment. Many roles also have generous time off and holidays, donation matching (up to $10,000), and a wide menu of extras like FSAs, commuter benefits, legal and identity-theft protection, pet insurance, and wellness discounts. Optional programs can include student-loan and home-purchase support, plus family care resources and expert medical services.