Senior System Software Engineer— Autonomous Driving Context Fusion

NVIDIA•Santa Clara, CA

About The Position

NVIDIA is seeking a Software Optimization Engineer for its DRIVE Road Structure / Online Mapping / Context Fusion team. The role focuses on improving the efficiency and real-time performance of software that combines perception, map, and localization data to build a consistent model of the driving environment. The engineer will collaborate 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. This work supports reliable autonomous driving capabilities within demanding compute and timing constraints.

Requirements

A PhD with 4 or more years, an MS with 6 or more years, or a BS (or equivalent experience) with 8 or more 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.
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, focused on preserving correctness and reliability.
Strong communication skills and ability to collaborate effectively across algorithm, software, and platform teams.

Nice To Haves

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.

Responsibilities

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 supported 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.