Senior Software Engineer, World Model – Autonomous Vehicles

This is a fully remote position, open to applicants in California, +1 more state.

📋 Description

• Develop and take ownership of the core online world model and context fusion software utilized in vehicles, overseeing everything from architecture to deployment.

• Write production-level C++ code for real-time embedded systems.

• Create software architecture, interfaces, and data flows for vehicle programs while adhering to CPU, memory, and latency constraints.

• Analyze pipelines, pinpoint bottlenecks, and enhance CPU efficiency, memory usage, and overall latency on NVIDIA DRIVE Orin and Thor.

• Establish benchmarks and conduct performance regression testing.

• Utilize CUDA GPU parallel processing for compute-intensive mapping components.

• Integrate mapping algorithms within NVIDIA’s autonomous vehicle framework.

• Adhere to ASIL-B/D automotive safety standards, employing static analysis, safety-focused coding practices, and thorough unit and integration testing.

• Strive for 100% line and branch coverage.

• Construct resilient software capable of handling diverse vehicle operating conditions and potential failure scenarios.

• Participate in code reviews and maintain quality and safety standards.

⛳️ Requirements

• 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 discipline, or equivalent experience.

• Over 5 years of experience in developing robust, production-quality software.

• At least 3 years of professional experience in modern C++ development.

• Strong understanding of memory management, concurrency, and performance optimization.

• Proven experience in profiling and optimizing CPU usage, memory consumption, and latency with the help of profilers and benchmarks.

• Knowledge of algorithms and data structures and their performance implications.

• Experience in designing software architecture and APIs for extensive, long-lasting codebases.

• Familiarity with static analysis, unit testing, and strategies for achieving high test coverage.

• Ability to collaborate with algorithm developers and comprehend their work.

• Experience in software development on embedded, real-time, or automotive platforms, including familiarity with RTOS, functional safety standards and practices, MISRA or AUTOSAR C++ guidelines, and safety-qualified toolchains.

• Proficient in GPGPU programming (CUDA) and GPU performance optimization.

• Knowledge of cache-aware data arrangements, memory allocation optimization, multithreading, or SIMD/vectorization.

• Experience with 3D geometry and graphics development.

• Background in creating efficient, reusable APIs and frameworks for complex systems.

🏝️ Benefits

• Equity

• Benefits