4 months ago
Berlin, GermanyStaff+
Responsibilities
- Set technical direction, architecture, engineering standards, and roadmap for the Perception & Autonomous Systems team.
- Remain approximately 50% hands-on by implementing software, conducting code reviews, and contributing to critical design decisions.
- Drive the computer vision stack using classical computer vision and hybrid CPU/CUDA perception and image-processing pipelines.
- Guide machine learning model integration, inference pipelines, quantization, runtime optimization, deployment, and training workflows.
- Shape the autonomous vehicle software architecture, including SOTIF considerations.
- Mentor engineers, coordinate with adjacent teams, resolve complex technical problems, and lead technical alignment.
- Participate in field testing and experimental validation activities.
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.
- Several years of experience in Data Engineering or designing scalable data-processing pipelines.
- Demonstrated technical leadership in architecture direction, engineering mentorship, 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 skills and the ability to guide an interdisciplinary engineering team.
- Fluent English is required; German is advantageous.
Benefits
- Flexible working hours accommodating personal responsibilities.
- Corporate Benefits discounts across fashion, beauty, travel, and culture.
- Subsidy for public transport tickets.
- Employer-funded further education and training.
- Excellent public transport connections at the Wedding location.
- Diverse, international team and work on socially relevant autonomous-mobility solutions.
- Face-to-face collaboration is expected; the company is not fully remote.
Tech Stack
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