Skills this job asks for
Machine learningDeep learningPythonC++PyTorchTensorFlowEnglish
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Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal: ask the recruiter.
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No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Before you apply
Sponsorship unknown
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
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About the role
We are looking for a Computer Vision and Machine Learning (CV/ML) Engineer to develop and deploy intelligent perception systems for our autonomous drone-in-a-box platform. You will work on challenging real-world computer vision problems, from real-time object detection and tracking on embedded devices to advanced scene understanding and cloud-based inference. As part of a small, technical team, you will own solutions across our software stack, taking algorithms and models from prototype to deployment. This position is for an on-site employee for our Zurich office.
Responsibilities
• Design and develop a wide variety of computer vision and machine learning features for real-time unmanned aerial vehicle (UAV) applications
• Train, fine-tune and evaluate deep learning models for tasks such as object detection, instance segmentation, image retrieval/reidentification
• Optimize algorithms and models for edge devices (NVIDIA Jetson and Qualcomm Dragonwing), and integrate them into our image and video processing pipelines
• Monitor ML model performance in real-world deployments and set up workflows for continuous improvement (data collection, curation, labeling, retraining, evaluation)
• Evaluate and integrate large/vision language models for scene understanding, situational awareness, and hazard analysis, including prompt design, performance benchmarking, and production deployment
Qualifications
• Degree in Computer Science, Robotics Engineering, Electrical Engineering, or a related field (or equivalent practical experience)
• Solid understanding of computer vision and machine learning fundamentals
• Strong programming skills in Python and C++, with experience developing production-grade software that powers CV/ML systems
• Experience with PyTorch or TensorFlow, ONNX, TensorRT, CUDA
• Experience with end-to-end model development: from dataset curation, labeling strategies, active learning workflows to deployment and optimization for edge devices
• Excellent oral and written skills in English
• Work permit in Switzerland required
Bonus Points
• Good understanding of 3D vision and robotics perception, along with hands-on experience with OpenCV and ROS/ROS2, is a strong plus
• Experience with NVIDIA Jetson and Qualcomm edge devices, and their CV/ML SDKs
• Experience with transformers, large/vision language models and prompt design for perception tasks
• Experience with GStreamer pipelines and custom plugin development
• Experience with AI-assisted development tools and coding agents (e.g., Claude Code, Codex, Cursor) in a professional setup to accelerate implementation, debugging, testing, and review
100% · On-site
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