Vision being the dominant human sense, eye tracking constitutes a powerful approach for understanding the human mind! At Pupil Labs, our mission is to provide cutting-edge eye-tracking solutions, which are more robust, accurate, accessible, and user-friendly than ever before. Already today, our products empower thousands of users in academia and industry, clinical surgeons, elite athletes, astronauts on the International Space Station, and many more. Unlocking the full potential of eye-tracking technology depends not only on solving complex research problems, but also on building robust, scalable tools that empower the entire development pipeline.
To support our efforts, we are looking to grow our Berlin-based team with a full-time Software Engineer – Computer Vision & Tooling who combines solid experience in classical computer vision with a strong engineering mindset. You will help take internal research tools and core vision components into production-ready systems, and build internal tools that streamline the development, curation, and evaluation of data pipelines. This is an on-site position (with up to two home-office days per week).
Pupil Labs offers a competitive salary, flexible work arrangements, a great team of coworkers, a young and dynamic company structure, and a culture of participation and feedback.
You are excited about joining an ambitious, international, diverse, interdisciplinary, young, enthusiastic, and talented team of researchers and software specialists? You have a growth mindset, thrive in fast-paced work environments, and enjoy building high-quality tools that support both people and products? Then we are looking forward to hearing from you!

• Develop and maintain core computer vision components, such as camera calibration, tracking, pose estimation, and projection logic.
• Translate research prototypes into robust, maintainable production code, with a focus on usability and performance.
• Design and implement internal tooling to support labeling, data inspection, model evaluation, and experiment tracking.
• Work across the ML and data engineering pipeline, helping to structure and manage large datasets, pre-processing routines, and automated workflows.
• Collaborate closely with researchers, engineers, and product teams to integrate your tools and systems into real-world pipelines.
• Help define and evolve our internal CV/ML infrastructure and coding standards.