3 months ago
Berlin, GermanyStaff+
Responsibilities
- Set technical direction, architecture, engineering standards, and roadmap for the Perception & Autonomous Systems team.
- Remain approximately 50% hands-on through implementation, code reviews, design work, and resolution of complex technical problems.
- 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 autonomous-vehicle software architecture, including SOTIF considerations, and mentor engineers on best practices.
- 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++ 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 scalable data-processing pipeline design.
- Proven technical leadership in 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 classical computer vision and image-processing knowledge.
- Experience with CUDA, GPU programming, MLOps, and inference frameworks such as TensorRT or ONNX Runtime is advantageous.
- Fluent English is required; German knowledge is advantageous.
Benefits
- Flexible working hours.
- Corporate Benefits partner discounts.
- Public transport ticket subsidy.
- Employer-funded further education and training.
- Attractive Wedding location with strong public transport connections.
- Face-to-face collaboration in a non-fully-remote company.
- Diverse, international, collaborative team environment.
Tech Stack
Categories
ML EngineeringRobotics
