Senior System Software Engineer – Embedded AI Inference

Senior System Software Engineer – Embedded AI Inference page is loaded## Senior System Software Engineer – Embedded AI Inferencelocations: Germany, Munichtime type: Full timeposted on: Posted Todayjob requisition id: JR 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).
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