We are looking for a Software Optimization Engineer to join our DRIVE Road Structure / Online Mapping / Context Fusion team. In this role, you will improve the efficiency and real-time performance of software that brings together perception, map, and localization data to build a consistent model of the driving environment. You will work closely with algorithm and platform engineers to identify bottlenecks, optimize software architecture and data flows, and deliver measurable improvements in CPU utilization, memory usage, and latency on automotive platforms. Your work will help advanced autonomous driving capabilities run reliably within demanding compute and timing constraints.
What you’ll be doing:
- Optimize context fusion software that integrates perception, map, and localization data to represent the driving environment.
- Design and refine software architecture, interfaces, and data flows to meet CPU, memory, and latency requirements on automotive platforms.
- Profile complex software pipelines, identify performance bottlenecks, and implement improvements backed by reproducible measurements.
- Work with algorithm teams to improve computational efficiency while preserving algorithm behavior, output quality, and correctness.
- Develop benchmarks and performance regression tests to track improvements and prevent regressions.
- Partner with perception, mapping, localization, and platform engineers to resolve system-level performance issues.
- Write reliable, maintainable code and contribute to code reviews, testing, and the safety and quality expectations of autonomous driving software.
What we need to see:
- A PhD with 4+ years, an MS with 6+ years, or a BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
- Strong proficiency in modern C++ and extensive experience designing and developing performance-sensitive software.
- Demonstrated ability to profile and optimize CPU utilization, memory consumption, and end-to-end latency.
- A strong understanding of data structures, algorithms, memory management, concurrency, and their impact on software performance.
- Experience using profiling tools and benchmarks to diagnose bottlenecks and validate improvements under representative workloads.
- A systematic approach to debugging and optimization, with a focus on preserving correctness and reliability.
- Strong communication skills and the ability to collaborate effectively across algorithm, software, and platform teams.
Ways to stand out from the crowd:
- Experience optimizing real-time software on embedded or automotive platforms.
- Familiarity with context fusion, map fusion, localization, perception pipelines, state estimation, or related ADAS and autonomous driving systems.
- Experience with cache-aware data layouts, memory allocation optimization, multithreading, or SIMD/vectorization.
- Experience designing efficient APIs and reusable software frameworks for complex systems.
- A track record of delivering measurable performance improvements in production software while preserving correctness, output quality, and reliability.
#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:184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
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.Skills Required
- PhD with 4+ years, MS with 6+ years, or BS/equivalent experience with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field
- Strong proficiency in modern C++
- Extensive experience designing and developing performance-sensitive software
- Experience profiling and optimizing CPU utilization, memory consumption, and end-to-end latency
- Strong understanding of data structures, algorithms, memory management, concurrency, and software performance
- Experience using profiling tools and benchmarks to diagnose bottlenecks and validate improvements under representative workloads
- Systematic approach to debugging and optimization focused on correctness and reliability
- Strong communication and cross-functional collaboration skills
- Experience optimizing real-time software on embedded or automotive platforms
- Familiarity with context fusion, map fusion, localization, perception pipelines, state estimation, ADAS, or autonomous driving systems
- Experience with cache-aware data layouts, memory allocation optimization, multithreading, or SIMD/vectorization
- Experience designing efficient APIs and reusable software frameworks for complex systems
- Track record of delivering measurable production software performance improvements while preserving correctness, output quality, and reliability
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Feedback suggests equity grants, stock options/RSUs, and a discounted ESPP materially boost total compensation and can deliver significant wealth-building when the stock performs well.
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Healthcare Strength — Feedback suggests medical, dental, and vision plans with in-network preventive care at 100%, telehealth, and concierge-style support are comprehensive and valued.
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Parental & Family Support — Feedback suggests up to 22 weeks fully paid parental leave, fertility coverage, and adoption/surrogacy reimbursement provide strong family-focused benefits.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
