Senior Deep Reinforcement Learning Engineer - Autonomous Driving

NVIDIA
Santa Clara
Full timeUSD 224,000 - 356,500 annuallyFunction: Education & TrainingExperience: 12+ yearsEducation: bachelorsSkills: ["Analytical and problem-solving","Implementing and debugging","Collaboration"]

Build and implement new reinforcement learning algorithms to drive autonomous vehicle decision-making and planning. Develop scalable RL training pipelines and simulation environments, and work with perception and planning teams to integrate RL models into the unified autonomous driving stack. Benchmark RL against imitation learning baselines, optimize and deploy models to production automotive hardware, and improve performance in complex urban environments.

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FursaFursa
NVIDIA
NVIDIA
4 days ago

Senior Deep Reinforcement Learning Engineer - Autonomous Driving

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Build and implement new reinforcement learning algorithms to drive autonomous vehicle decision-making and planning. Develop scalable RL training pipelines and simulation environments, and work with perception and planning teams to integrate RL models into the unified autonomous driving stack. Benchmark RL against imitation learning baselines, optimize and deploy models to production automotive hardware, and improve performance in complex urban environments.
Location: Santa Clara
Employment Type: Full time
Job Function: Education & Training
Seniority: Mid level

Key Responsibilities

  • •Build and implement 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.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually
Equity and Bonus:Equity

Key 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.
  • •Strong background in reinforcement learning, including policy gradient methods (PPO, GRPO) and actor-critic architectures for on-policy and off-policy RL.
  • •Proficiency in PyTorch or TensorFlow with real experience applying RL algorithms.
  • •Experience in C++ and Python development for real-time systems and strong debugging/analytical skills.
Experience:12+ yearsAutonomous driving
Education:Bachelor's
Skills:Analytical and problem-solvingImplementing and debuggingCollaboration
Tech Stack:Reinforcement LearningPolicy gradientPPOGRPOActor-critic architecturesOn-policy RLOff-policy RLPyTorchTensorFlowC++PythonImitation learningSimulation environments

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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