Computer Vision and Machine Learning Engineer

Sunflower Labs GmbH; Stallikon; On-site; CHF 120,000 - 180,000; Full time

Job summary

Sunflower Labs GmbH in Zürich, Switzerland is seeking a Computer Vision and Machine Learning Engineer to build and deploy intelligent perception for our autonomous drone-in-a-box platform. You will tackle real-time object detection, tracking on embedded devices, and scene understanding from prototype to production.

As part of a small, technical team you will own end-to-end solutions across the software stack, optimize for edge devices (Jetson/Dragonwing), and contribute to cloud inference, data

Qualifications

• Degree in Computer Science, Robotics, Electrical Engineering, or equivalent.
• Strong CV/ML fundamentals.
• Proficiency in Python and C++ for production systems.

Responsibilities

• Design and develop real-time computer vision features for UAV applications.
• Train, fine-tune and evaluate deep learning models for object detection, segmentation, and image retrieval.
• Optimize algorithms for edge devices and integrate into image/video pipelines.
• Monitor model performance in deployments and establish improvement workflows.
• Evaluate and integrate large/vision-language models for scene understanding and deployment.

Skills

Python

C++

CV/ML fundamentals

PyTorch/TensorFlow

ONNX/TensorRT/CUDA

Edge device optimization

English communication

Education

Degree in Computer Science / Robotics / Electrical Engineering

Tools

NVIDIA Jetson

OpenCV

GStreamer

ROS/ROS2

CUDA

Job description

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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