Senior Software Engineer - ADAS

Senior Software Engineer - ADAS

NVIDIA GmbH

München
C++
Python
ADAS
deep learning
GPU optimization
sensor fusion
real-time systems
Linux
machine learning
automotive

Hexjobs Insights

NVIDIA is hiring a Senior Software Engineer for ADAS in Munich. Responsibilities include developing C++ functions, integrating deep learning models, and optimizing performance. Requires 4-8 years of experience and expertise in C++ and Python.

Schlüsselwörter

C++
Python
ADAS
deep learning
GPU optimization
sensor fusion
real-time systems
Linux
machine learning
automotive

Introduction

Step into the future with NVIDIA, a global leader in AI computing, data science, and graphics, driving innovation in Artificial Intelligence, Deep Learning, and Autonomous Vehicles. Our team of visionaries is reshaping industries worldwide with cutting-edge technologies. Join us on an exhilarating journey as a Senior Software Engineer, where you'll fuse our ADAS software stack with OEM applications, witnessing your creations hit the road in real-time. You would have opportunity to bring cutting Edge AI Models to Futuristic Cars. 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 mid-level Software Engineer to develop production ADAS and autonomous driving functions in C++ and Python. If you're passionate about building robust, high-performance features that run on GPUs in real vehicles, we'd like to hear from you.

What you'll be doing:

*Design, implement, and maintainC++ ADAS functions for perception, prediction, and planning (e.g., lane keeping, ACC, AEB, traffic-light and object handling) in a safety-critical codebase.

  • Integrate deep learning models into C++ pipelines: take models trained in Python (PyTorch or TensorFlow), export/convert them, and deploy them for real-time inference on NVIDIA GPUs.
  • Work with multi-sensor data - cameras, radar, lidar - and implement sensor fusion, tracking, and decision-making logic in C++.
  • 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.
  • Contribute to tooling around data quality, automated evaluation, and regression tests for ADAS functions.
  • Collaborate closely with ML researchers, systems engineers, and automotive partners to turn prototype algorithms into production-ready C++ implementations.

What we need to see:

*4-8 years of professional software engineering experience, ideally inADAS, automotive, robotics, or real-time systems.

  • Master's or PhD degree in Computer Science or in 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 training and using deep learning models (PyTorch or TensorFlow): designing experiments, tuning hyperparameters, working with large datasets, and debugging model behavior.
  • Experience developing on Linux: build systems (CMake), debugging (gdb, sanitizers), profiling, and git-based workflows in a CI/CD environment.
  • Familiarity with one or more of:
  • GPU programming and optimization (CUDA, TensorRT, cuDNN)
  • Computer vision / perception (object detection, segmentation, multi-object tracking)
  • Robotics or autonomous systems (ROS/ROS2, ADAS features, simulation environments)

Ways to stand out from the crowd:
*Direct experience implementingADAS functions in C++, such as lane keeping, adaptive cruise control, automatic emergency braking, or traffic-sign/traffic-light handling.

  • Experience with camera calibration, sensor fusion, or multi-camera perception systems.
  • Knowledge of model optimization and deployment: quantization (INT8, FP8, 4-bit), TensorRT-LLM, ONNX Runtime, or similar frameworks.
  • Background in training infrastructure: distributed training, experiment tracking, dataset versioning, hyperparameter optimization.
  • 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 ADAS and autonomous driving problems where your C++ and ML skills directly impact vehicle safety and performance. 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.

We offer

Germany, Munich

Full time

2026-03-04

Posted Yesterday

JR2013471

Contact

If this opportunity aligns with your background and interests, please apply with your resume and a brief description of relevant ADAS or autonomy projects (links to GitHub, publications, or technical write-ups are welcome)

Aufrufe: 8
Veröffentlichtvor 11 Tagen
Läuft abin 19 Tagen
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