Senior System Software Engineer - Embedded AI Inference

Standort:

• München

Nvidia Jetzt bewerben

Zusammenfassung

• Arbeitszeit Vollzeit
• Typ Festanstellung
• Qualifikationslevel Hochschultätigkeiten

Gewünschte Fähigkeiten & Kenntnisse

Machine Learning Socia-Media-Tool Design Edge Software-Engineering Programmiererfahrung LORA CMake MCP Open Source C Python Solid Code-Review Analyse GIT Entwicklungsumgebungen Debugging GitHub Linux Continuous Integration Compute Unified Device Architecture Engineering

Stellenbeschreibung

Senior System Software Engineer - Embedded AI Inference

Germany, Munich

Full time

2026-03-20

Posted Yesterday

JR2015026

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).

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Profil

Fachliche Voraussetzung

• Algorithmus, Automobilindustrie, Automotive Software, Autonome Fahrzeuge, C , CUDA, Cmake, Code-Review, Codeanalyse, Continuous Integration, Daten-Pipeline, Debugging, Deep Learning, Dekodierung, Echtzeitsysteme, Forschung, GPGPU, Git, Gpu Programming, Grafikprozessor, Informatik, Künstliche Intelligenz, Large Language Models, Linux, Machine Learning, Montage und Demontage, Multidisziplinärer Ansatz, Netzwerkleistung, Open Source, Profiling, Prototyping, Python, Pytorch, Robotics, Sicherheitskritische, Software Quality, Softwareentwicklung, Systems Engineering, Systemsoftware, Unit Testing, Workflows

Persönliche Fähigkeiten

• Freundlichkeit, Lösungsorientiert

Schulabschluss

• Master

Berufserfahrung

• Mit Berufserfahrung

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Bewerbung

Jetzt bewerben

Branche:

Handel

Arbeitgeber:

Nvidia

Adresse:

Nvidia

Rosenheimer Str 145 B

81671 Munchen

Web:

http://nvidia.de