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Senior System Software Engineer— Autonomous Driving Context Fusion

NVIDIA

Santa Clara, CAFull-time$184–357K/yrPosted 1w agoStill listed 1 day ago

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At a glance

Compensation
$184–357K/yr
Location
Santa Clara, CA
Schedule
Full-time
Work Authorization
Not specified

Olive focuses on jobs in the United States, including remote roles you can work from there.

Job overview

NVIDIA seeks a Software Optimization Engineer for its DRIVE Road Structure, Online Mapping, and Context Fusion team. The engineer will improve the efficiency and real-time performance of software combining perception, map, and localization data for autonomous driving. The role focuses on profiling and optimizing software architecture and data flows, delivering measurable performance improvements on automotive platforms, and collaborating with algorithm and platform engineers.

Skills & qualifications

RequiredNice to have

Skills

Modern C++, requiredPerformance-Sensitive Software, requiredCPU Optimization, requiredMemory Optimization, requiredLatency Optimization, requiredData Structures, requiredAlgorithms, requiredMemory Management, requiredConcurrency, requiredProfiling Tools, requiredBenchmarking, requiredDebugging, requiredCommunication, requiredCross-Functional Collaboration, requiredReal-Time Software Optimization, nice to haveEmbedded Platforms, nice to haveAutomotive Platforms, nice to haveContext Fusion, nice to haveMap Fusion, nice to haveLocalization, nice to havePerception Pipelines, nice to haveState Estimation, nice to haveADAS, nice to haveAutonomous Driving Systems, nice to haveCache-Aware Data Layouts, nice to haveMemory Allocation Optimization, nice to haveMultithreading, nice to haveSIMD Vectorization, nice to haveAPI Design, nice to haveSoftware Framework Design, nice to have

Qualifications

PhD+4, MS+6, BS+8 or Equivalent, required4+ Years Relevant Experience, required6+ Years Relevant Experience, required8+ Years Relevant Experience, required

Full job description

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.

Applications for this job will be accepted at least until November 7, 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.

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