2 months ago
Berlin, GermanyStaff+
Responsibilities
- Lead the Perception & Autonomous Systems team’s technical direction, architecture, engineering standards, and roadmap.
- Remain approximately 50% hands-on through implementation, code reviews, and critical design work.
- Drive the computer vision stack using classical computer vision and hybrid CPU/CUDA processing pipelines.
- Guide machine learning model integration, inference pipelines, runtime optimization, quantization, and model deployment and training workflows.
- Shape the autonomous vehicle software architecture, including SOTIF considerations.
- Mentor engineers, coordinate with adjacent teams, and participate in field testing and experimental validation.
Requirements
- Bachelor's or Master's degree in Computer Science, Robotics, Machine Learning, Computer Vision, or a related technical discipline.
- At least 8 years of professional experience in modern C++ software development for high-performance or real-time systems.
- At least 8 years of experience in Machine Learning Engineering, Computer Vision, or deploying machine learning models in production environments.
- Several years of experience in Data Engineering or designing scalable data processing pipelines.
- Demonstrated technical leadership through architecture direction, mentoring, cross-functional alignment, and hands-on coding and design.
- Strong expertise in modern C++, software architecture, ROS2, and performance optimization, with solid knowledge of classical computer vision and image processing.
- Experience with CUDA, GPU programming, MLOps, and inference optimization frameworks such as TensorRT or ONNX Runtime is advantageous.
- Strong analytical and structured problem-solving abilities and the ability to guide an interdisciplinary engineering team.
- Fluent English is required; German language knowledge is advantageous.
Benefits
- Flexible working hours.
- Corporate Benefits partner discounts.
- Public transport ticket subsidy.
- Company-funded further education and training.
- Excellent public transport connections at the Wedding location.
- Face-to-face collaboration in a non-fully-remote work environment.
- Diversity-focused workplace that explicitly encourages applications from women.
Tech Stack
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