Profile complex pipelines, find bottlenecks, and deliver measurable improvements in CPU utilization, memory usage, and end-to-end latency, backed by reproducible measurements on Orin and Thor.
Develop benchmarks and performance regression tests that track improvements and prevent regressions.
Use GPU parallelism (CUDA) where it helps to accelerate compute-heavy mapping components.
Implement and integrate algorithmic solutions from the mapping team into NVIDIA’s AV stack, working closely with algorithm engineers to understand and refine them while preserving behavior, output quality, and correctness.
Develop to automotive safety standards (ASIL-B/D): apply strong static analysis, follow safety-oriented coding guidelines, and achieve 100% line and branch coverage with rigorous unit and integration tests.
Build software that is robust to the varied conditions and failure modes of vehicles operating around the world.
Contribute to code reviews and uphold the team’s quality and safety expectations.
What we need to see
PhD with 1+ year, MS with 3+ years, or BS with 5+ years of relevant experience in Computer Science, Electrical or Computer Engineering, or a related field, or equivalent experience.
5+ years of experience building robust, production-quality software
3+ years of professional modern C++ development, with a strong grasp of memory management, concurrency, and performance.
Demonstrated ability to profile and optimize CPU utilization, memory consumption, and latency using profilers and benchmarks under representative workloads.
Solid understanding of algorithms and data structures and their impact on performance.
Experience designing software architecture and APIs for large, long-lived codebases.
A quality-first, systematic approach to debugging and optimization: comfort with static analysis, unit testing, and high-coverage test strategies.
Ability to work with algorithm developers and understand their work.
Strong communication and analytical skills, and the ability to collaborate effectively across multiple teams.
Autonomous and responsible, a strong team player who enjoys solving hard problems, with a passion for robotics and autonomous vehicles.
Ways to stand out from the crowd
Software development on embedded, real-time, or automotive platforms, including RTOS experience (e.g., QNX, Linux RT), experience with functional safety standards and processes (ISO 26262, ASIL-B/D), MISRA or AUTOSAR C++ guidelines, and safety-qualified toolchains.
GPGPU programming (CUDA) and GPU performance tuning.
Cache-aware data layouts, memory allocation optimization, multithreading, or SIMD/vectorization.
Experience with 3D geometry and graphics.
Experience building efficient, reusable APIs and frameworks for complex systems.
#AutonomousVehicles
- Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
- 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 November 13, 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.