Senior RL Engineer, Autonomous Driving & Production AI

NVIDIA AI; Santa Clara (CA); On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Santa Clara, CA, is seeking a Reinforcement Learning Engineer to build and deploy RL algorithms for autonomous vehicle decision-making and planning, and to develop scalable training pipelines and simulation environments.

You'll collaborate with perception and planning teams to integrate RL models into the autonomous driving stack, benchmark against imitation learning baselines, and deploy to automotive hardware.

Qualifications

• BS or higher in Computer Science, Robotics, Electrical Engineering, or 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 algorithm
• 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.

Responsibilities

• Build and implement brand 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 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.

Skills

Reinforcement Learning

Policy gradient methods

Actor-critic architectures

On-policy RL

Off-policy RL

PyTorch or TensorFlow

C++ and Python

Real-time systems

Education

BS or higher in CS/Robotics/EE or related field

Tools

PyTorch

TensorFlow

C++

Python

Job description

NVIDIA in Santa Clara, CA, is seeking a Reinforcement Learning Engineer to build and deploy RL algorithms for autonomous vehicle decision-making and planning, and to develop scalable training pipelines and simulation environments.

You'll collaborate with perception and planning teams to integrate RL models into the autonomous driving stack, benchmark against imitation learning baselines, and deploy to automotive hardware.