10 days ago
Zürich, SwitzerlandSenior
Responsibilities
- Design, implement, and optimize real-time onboard perception algorithms for detection, temporal association, and state estimation.
- Train, retrain, and evaluate neural networks for detection and classification, including dataset curation, labeling strategy, and evaluation methodology.
- Optimize models and inference pipelines for embedded hardware under latency, throughput, and compute constraints.
- Develop camera calibration and sensor synchronization procedures for multi-camera and multi-sensor systems.
- Fuse visual measurements with inertial and platform-state data using filtering and estimation techniques.
- Plan and execute field tests, flight campaigns, and deployment improvements using real-world logs and video.
- Build repeatable evaluation and regression methods for measuring perception performance and accuracy.
- Evaluate cameras, lenses, sensors, and compute hardware against real performance data.
- Own computer vision deliverables end to end, align requirements across teams, and communicate with stakeholders and customers.
- Mentor and coach other engineers and improve product quality.
Requirements
- A degree in Computer Science, Electrical Engineering, Robotics, or a related field, or equivalent practical experience.
- Hands-on experience deploying computer vision systems on resource-constrained platforms, ideally robotic or aerial systems.
- Strong knowledge of classical computer vision, including feature detection and matching, optical flow, camera models and calibration, and multiple-view geometry.
- Practical experience training and deploying convolutional neural networks for detection or classification, including data collection, labeling quality, retraining, and evaluation.
- Experience debugging timing, synchronization, timestamp, exposure, and latency issues across sensors.
- Proficiency in C++, Python, and OpenCV.
- Experience taking computer vision work from problem definition through real deployment.
- Willingness and ability to perform field work, travel to test sites, and debug real-world logs and video.
- Ability to lead across teams, navigate ambiguity, and collaborate with engineering, product, and external stakeholders.
- EU citizenship is required.
- Preferred experience includes state estimation, sensor fusion, Kalman and extended Kalman filters, IMU integration, visual-inertial odometry, visual SLAM, ROS2, embedded inference runtimes, quantization, pruning, GPU or NPU acceleration, hardware-in-the-loop testing, PX4, and MAVLink-based systems.
Benefits
- Flexible working hours.
- Stock options.
- Generous holiday allowance.
- Company pension plan.
- Car parking.
- Enhanced maternity and paternity leave.
- Mental health and wellbeing support.
- Learning and development opportunities.
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