Senior RL Engineer – Autonomous Driving Systems

NVIDIA; United States; On-site; USD 224,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Reinforcement Learning Engineer to help advance autonomous driving technology using cutting-edge RL methods. This role focuses on building algorithms, scalable training environments, and integrating models with perception and planning components.

You will optimize RL models for production hardware, benchmark against baselines, and contribute to a robust, safe, and efficient autonomous driving stack across real-world scenarios.

Qualifications

• BS or higher in Computer Science, Robotics, Electrical Engineering, or related field
• 12+ years of experience in the related field
• Strong background in Reinforcement Learning, including policy gradient methods (PPO, GRPO), actor-critic architectures, on-policy and off-policy RL

Responsibilities

• Build and implement brand new 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.

Skills

Reinforcement Learning

PyTorch

C++

Python

Real-time systems

Education

BS or higher in CS/Robotics/EE

Tools

TensorFlow

Job description

NVIDIA is seeking a Reinforcement Learning Engineer to help advance autonomous driving technology using cutting-edge RL methods. This role focuses on building algorithms, scalable training environments, and integrating models with perception and planning components.

You will optimize RL models for production hardware, benchmark against baselines, and contribute to a robust, safe, and efficient autonomous driving stack across real-world scenarios.