Computer Vision and Machine Learning Engineer

Sunflower Labs GmbH

Stallikon

On-site

CHF 110,000 - 150,000

Full time

14 days+

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Job summary

Sunflower Labs GmbH in Zürich is seeking a computer vision and machine learning engineer to enhance the perception capabilities of our autonomous drone-in-a-box system. You will join a focused CV/ML team and contribute to moving algorithms from prototype to deployment in the field, on-site at our Zurich office.

The role emphasizes real-time CV/ML development, edge optimization for NVIDIA Jetson/DragonWing, and integration of vision-language models for scene understanding and hazard analysis.

Qualifications

  • Degree in Computer Science, Electrical Engineering, Robotics Engineering, or related field (or equivalent practical experience).
  • Solid understanding of computer vision and machine learning fundamentals.
  • Strong programming skills in Python and C++.
  • Experience with PyTorch or TensorFlow, OpenCV, ROS/ROS2, CUDA, TensorRT.
  • Experience with end-to-end model development: dataset curation, labeling strategies, active learning workflows to deployment and optimization for edge devices.

Responsibilities

  • Design and develop computer vision and machine learning features for real-time UAV applications.
  • Train, fine-tune and evaluate deep learning models for object detection, segmentation, and retrieval.
  • Optimize algorithms for edge devices (NVIDIA Jetson and Qualcomm DragonWing) and integrate into image/video pipelines.
  • Monitor ML model performance in real deployments and establish data collection, labeling, retraining, and evaluation workflows.
  • Integrate large/vision-language models and design queries for scene understanding, situational awareness and hazard analysis.

Skills

Python
C++
Computer vision
Deep learning
PyTorch
TensorFlow
OpenCV
ROS/ROS2
CUDA
Edge deployment

Education

Bachelor's degree in CS/EE/Robotics or equivalent

Tools

NVIDIA Jetson
Qualcomm DragonWing
TensorRT
GStreamer

Job description

We are looking for a computer vision and machine learning (CV/ML) engineer to enhance the perception capabilities of our fully autonomous drone-in-a-box system. You will be joining a small, CV/ML focused team and be one of the core contributors to our software stack, taking algorithms and models from prototype to deployment on the systems in the field. This position is for an on-site employee for our Zurich office.

Tasks
  • 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, semantic 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 performances in real world deployments and set up workflows for continuous improvement (data collection, curation, labeling, retraining, evaluation)

  • Integrate large/vision language models into our system, and design, test and maintain queries for tasks like scene understanding, situational awareness and hazard analysis

Requirements
  • Degree in Computer Science, Electrical Engineering, Robotics 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++

  • Experience with PyTorch or TensorFlow, OpenCV, ROS/ROS2, CUDA, TensorRT

  • Experience with end-to-end model development: from dataset curation, labeling strategies, active learning workflows to deployment and optimization for edge devices

  • Experience with transformers, large/vision language models and prompt design for perception tasks is a plus

  • Experience with GStreamer pipelines and custom plugin development is a plus

  • Experience with Qualcomm edge devices and CV/ML SDKs is a plus

  • Good oral and written skills in English

  • Work permit in Switzerland required

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