Job description

NVIDIA is seeking a highly motivated Software Engineer to join our Autonomous Vehicle (AV) Simulation team. In this role, you will help build and scale realistic virtual environments that accelerate the training, testing, and validation of NVIDIA’s autonomous driving software stack. Our mission is to enable large-scale simulation and debugging of AV algorithms across millions of scenarios per day, spanning diverse traffic patterns, road conditions, weather environments, and edge cases. Achieving this requires deep performance optimization and systems-level analysis across the entire software stack — from AV algorithms and AI models to system software, infrastructure, and production-scale simulation workflows. What you’ll be doing: • Develop scalable simulation platforms and workflows for autonomous driving validation and training. • Work on Real2Sim and Sim2Real domain adaptation technologies to transform real-world driving incidents into diverse simulation scenarios — and bridge the gap between simulated and real-world behavior. • Contribute across a multidisciplinary stack involving: System software and distributed infrastructure, neural graphics & rendering, generative AI & synthetic data generation, computer vision & deep learning, and real-to-synthetic domain adaptation. • Optimize large-scale simulation workflows for performance, scalability, reliability, and production deployment. • Collaborate closely with researchers, infrastructure engineers, and product teams across NVIDIA. • Drive technology transfer into production products and contribute to open-source initiatives where applicable. What we need to see: • BS, MS, or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or a related field (or equivalent experience). • 5+ years of relevant autonomous vehicles industry experience. • Strong programming skills in Python, C/C++, PyTorch, and Linux/bash scripting. • Experience with modern software engineering and infrastructure tools such as Docker, Bazel, Jenkins, CI/CD pipelines, and distributed systems tooling. • Strong background in computer vision, deep learning, simulation systems, or related domains. • Excellent analytical and mathematical problem-solving skills. • Ability to independently drive complex projects from concept to production. • Strong communication, collaboration, and teamwork skills. • Experience in machine learning, large-scale systems, analytics, statistics, or applied mathematics. Ways to stand out from the crowd: • First-author publications at top-tier conferences such as NeurIPS, CVPR, ICCV, ECCV, or ICML. • Experience in autonomous driving, robotics simulation, neural rendering, synthetic data generation, or generative AI. • Proven research or engineering excellence through internships, open-source contributions, code competitions, or impactful production systems. • Experience optimizing high-performance or large-scale distributed workloads. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Develop scalable simulation platforms and workflows for autonomous driving validation and training.
Work on Real2Sim and Sim2Real domain adaptation technologies to transform real-world driving incidents into diverse simulation scenarios — and bridge the gap between simulated and real-world behavior.
Optimize large-scale simulation workflows for performance, scalability, reliability, and production deployment.
Collaborate closely with researchers, infrastructure engineers, and product teams across NVIDIA.
Drive technology transfer into production products and contribute to open-source initiatives where applicable.
BS, MS, or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or a related field (or equivalent experience).
5+ years of relevant autonomous vehicles industry experience.
Strong programming skills in Python, C/C++, PyTorch, and Linux/bash scripting.
Experience with modern software engineering and infrastructure tools such as Docker, Bazel, Jenkins, CI/CD pipelines, and distributed systems tooling.
Strong background in computer vision, deep learning, simulation systems, or related domains.
Excellent analytical and mathematical problem-solving skills.
Ability to independently drive complex projects from concept to production.
Strong communication, collaboration, and teamwork skills.
Experience in machine learning, large-scale systems, analytics, statistics, or applied mathematics.
First-author publications at top-tier conferences such as NeurIPS, CVPR, ICCV, ECCV, or ICML.
Experience in autonomous driving, robotics simulation, neural rendering, synthetic data generation, or generative AI.
Proven research or engineering excellence through internships, open-source contributions, code competitions, or impactful production systems.
Experience optimizing high-performance or large-scale distributed workloads.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 18, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aipythondockerci/cdmachine learning

Platform: eightfold
Effort: medium

Benefits

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