Senior Computer Vision & Deep Learning Engineer

We are partnering with a high-growth organization developing advanced autonomous solutions. You will contribute to the design and deployment of perception systems that operate in real-time enabling intelligent behavior in robotic machines.

This role suits someone who enjoys both algorithm innovation and hands-on product delivery: from data pipelines and model optimization to on-machine testing and validation.

Key responsibilities

• Develop and optimize deep-learning-based perception modules for real-time operation (detection, segmentation, tracking)
• Build robust pipelines from data generation model training deployment into production hardware
• Benchmark accuracy, latency and robustness on real robotic platforms contribute to continuous field validation
• Support broader autonomy stack through cross-team collaboration (localization, planning, UI)
• Contribute to documentation, testing and code standards to ensure long-term maintainability
• Provide mentorship within the perception team and participate in technical hiring decisions

Core experience (must-haves)

• Strong background in deep learning for computer vision (2D or multi-modal sensor input)
• Hands-on experience implementing perception models in C++ and/or Python on Linux systems
• Familiarity with real-time constraints and performance optimization techniques for deployed AI systems
• Experience with modern training frameworks (PyTorch, TensorFlow, etc.) and classical CV tools (OpenCV, PCL, etc.)
• Ability to scope work, manage priorities, and deliver in a fast-moving product organization
• Solid communication skills for cross-disciplinary technical work

Desirable (nice to have)

• Experience with LiDAR / radar fusion and 3D scene understanding
• Familiarity with GPU-accelerated inference pipelines and embedded deployment (CUDA, TensorRT, or similar)
• Exposure to robotics middleware (ROS/ROS2) and on-machine software integration
• Previous experience in industrial outdoor or safety-critical machine applications
• Rust programming for performance-critical components (optional)

Qualifications & languages

• Degree in Computer Science, Robotics, Electronic Engineering, Mechatronics or related discipline (or equivalent practical experience)
• Fluent in English. German is advantageous but not essential

Whats on offer

• Real influence on deployed robotic systems in operational environments
• Close-knit engineering teams and rapid iteration cycles
• The chance to push forward perception-driven automation in an emerging global market