NS
ML Engineer - 3D Perception (C++ / Python / Deep Learning)
Nicholson SAS
Karlsruhe · On-site 1w ago
About the role
About
I am currently hiring on behalf of a high-growth deep tech company operating at the intersection of Physical AI and real-world perception systems.
This team is building large-scale machine learning systems that interpret complex 3D environments in real time. If you enjoy solving hard perception problems and working close to production systems, this could be a strong fit.
Responsibilities
- Improving core 3D perception tasks: object detection, tracking, segmentation, and freespace estimation
- Designing and scaling auto-labelling pipelines to reduce manual annotation costs and increase dataset diversity
- Implementing robust tracking-by-detection algorithms in 3D space
- Training and optimising large ML models using substantial in-house compute infrastructure
Requirements
- MSc or PhD in Computer Science, Robotics, or a related discipline (or equivalent industry experience)
- Strong deep learning experience in at least one sensor modality (Camera, LiDAR, or Radar)
- Experience with modern architectures (transformer-based models preferred)
- Strong programming skills in C++ and Python
- Collaborative mindset and strong problem-solving ability
Nice to have
- Experience with TensorRT, LibTorch, or ONNX for optimised deployment
- Background working on mid-to-large-scale production software systems
This is an opportunity to join a highly technical team solving complex real-world perception challenges with meaningful compute resources and long-term product vision.
Location: Karlsruhe | On-site Employment Type: Full-time
Requirements
- Strong deep learning experience in at least one sensor modality (Camera, LiDAR, or Radar)
- Experience with modern architectures (transformer-based models preferred)
- Strong programming skills in C++ and Python
- Collaborative mindset and strong problem-solving ability
Responsibilities
- Improving core 3D perception tasks: object detection, tracking, segmentation, and freespace estimation
- Designing and scaling auto-labelling pipelines to reduce manual annotation costs and increase dataset diversity
- Implementing robust tracking-by-detection algorithms in 3D space
- Training and optimising large ML models using substantial in-house compute infrastructure
Skills
C++LiDARPythonRadarTransformer
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