Senior Software Engineer - Autonomous Driving Simulation

NVIDIA•Santa Clara, CA

2d•$152,000 - $287,500

About The Position

NVIDIA is seeking a highly motivated Software Engineer to join its Autonomous Vehicle (AV) Simulation team. The role focuses on building and scaling realistic virtual environments that accelerate the training, testing, and validation of NVIDIA’s autonomous driving software stack. The team enables large-scale simulation and debugging of AV algorithms across millions of scenarios per day, covering diverse traffic patterns, road conditions, weather environments, and edge cases. This work requires performance optimization and systems-level analysis across AV algorithms and AI models, system software, infrastructure, and production-scale simulation workflows. The engineer will develop scalable simulation platforms and workflows; work on Real2Sim and Sim2Real domain adaptation; and contribute across system software and distributed infrastructure, neural graphics and rendering, generative AI and synthetic data generation, computer vision and deep learning, and real-to-synthetic domain adaptation. The role also includes optimizing workflows for production deployment, collaborating across NVIDIA, and driving technology transfer into products and open-source initiatives where applicable. The position requires a relevant degree or equivalent experience, at least five years of relevant autonomous-vehicle industry experience, strong programming and software-infrastructure skills, and a background in computer vision, deep learning, simulation systems, or related fields. Compensation includes a base salary range of $152,000–$241,500 for Level 3 or $184,000–$287,500 for Level 4, depending on location, experience, and pay for similar positions. The employee will also be eligible for equity and benefits. Applications will be accepted at least until October 18, 2026. The posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.

Requirements

BS, MS, or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or a related field, or equivalent experience.
At least 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.

Nice To Haves

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.

Responsibilities

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 to system software and distributed infrastructure, neural graphics and rendering, generative AI and synthetic data generation, computer vision and deep learning, and real-to-synthetic domain adaptation.
Optimize large-scale simulation workflows for performance, scalability, reliability, and production deployment.
Collaborate with researchers, infrastructure engineers, and product teams across NVIDIA.
Drive technology transfer into production products and contribute to open-source initiatives where applicable.