NVIDIA is synonymous with innovation, boasting trailblazers who are shaping the world with their forward-thinking approaches. This is your chance to be part of a vibrant community that's redefining the technological landscape. Ready to shape the future of automotive technology with NVIDIA? Apply now to be part of a team that's revolutionizing the industry and driving innovation to new heights. Your potential awaits!
We're hiring a Senior Software Engineer to develop production automotive software for AI inference and agent orchestration in C++. Join us on an exhilarating journey, where you'll build out the foundation for next-generation automotive software applications: in-car agentic AI and inference of cutting-edge AI models (LLM, VLM, VLA). You would have the opportunity to shape cutting-edge AI frameworks that enable unprecedented in-car AI experiences and provide a reliable backbone for a new generation of Autonomous Vehicles.
If you're passionate about building robust, high-performance AI systems that run on GPUs in real vehicles, we'd like to hear from you.
What you'll be doing
- Design, implement, and maintain C++ agentic AI and AI inference solutions for embedded production platforms.
- Integrate PyTorch Deep Learning models into C++ pipelines, and deploy them for real-time inference on NVIDIA GPUs.
- Build and extend testable, modular libraries and components, including interfaces to models, sensor drivers, and vehicle control.
- Profile, debug, and optimize C++ and CUDA code to meet strict latency and throughput targets.
- Collaborate closely with ML researchers, systems engineers, and automotive partners to turn prototype algorithms into production-ready implementations.
What we need to see
- 8+ years of professional software engineering experience, ideally in high-performance safety-critical software, automotive, robotics, or real-time systems.
- Master's or PhD degree in Computer Science or Machine Learning.
- Strong modern C++ (C++14/17 or later): templates, RAII, smart pointers, STL, and experience building large codebases.
- Solid Python skills for tooling, training scripts, and glue code between data pipelines and C++ components.
- Hands-on experience building agentic AI frameworks and with LLM / VLM inference. Experience with LLM and VLM inference and related optimization techniques like speculative decoding, LoRA, MoE.
- Experience developing on Linux: build systems (CMake), debugging (gdb, sanitizers), profiling, and git-based workflows in a CI/CD environment.
- Familiarity with GPU programming and optimization, ideally with TensorRT.
Ways to stand out from the crowd
- Experience with agentic AI, specifically agents based on edge-friendly models (2–7B), including context management, reliable tool calling, and MCP, as well as experience with agentic coding.
- Direct experience with the NVIDIA DRIVE AGX platform.
- Knowledge of AI model optimization and deployment: quantization (INT8, FP8, 4-bit).
- Familiarity with high-performance LLM inference frameworks like TensorRT-LLM or ONNX Runtime.
- Understanding of software quality practices for safety-critical systems (code review, unit testing, static analysis; automotive standards knowledge is a plus) as well as open-source contributions or published work in AI, robotics, or GPU computing.
Work on challenging, real-world in-car AI inference problems where your ML and C++ skills directly impact the cabin experience and vehicle's self-driving capabilities. Collaborate with a talented, multidisciplinary team of researchers, engineers, and automotive experts. Solve hard technical problems at the intersection of deep learning, real-time systems, and production software engineering.
If this opportunity aligns with your background and interests, please apply with your resume and a brief description of relevant automotive AI projects (links to GitHub, publications, or technical write-ups are welcome).