Applied ML/Computer Vision Intern at a YC Backed Startup

At Cerrion, we’re building the future of AI-enabled manufacturing. Headquartered in Zurich and backed by Y Combinator and top Silicon Valley investors, we’re building a platform to deploy video AI Agents that can see what’s happening on the production floor, automatically spot problems, and instantly intervene to keep lines running smoothly, at scale. Our technology is live in factories across 15 countries, helping leading manufacturers in glass, beverage, food, CPG, building materials and wood cut downtime by up to 50%. We’ve reached an exciting inflection point — and we’re accelerating fast.

We’re hiring an Applied ML / Computer Vision Intern to help improve real-world vision systems deployed across more than 50 factories. You’ll dig into model and data failures end-to-end — from datasets, labels, and augmentations to training dynamics and evaluation — identify the root causes of recurring errors, and implement focused fixes in Python. Working alongside our research and operations teams, you’ll follow an established process, propose practical improvements, and validate them with targeted evaluations. This role is a great fit for someone with a computer vision and Python background who enjoys tracing problems through the full ML stack and turning findings into measurable system improvements.

• Model and Data Failure Analysis: Investigate failure cases across datasets, labels, augmentations, sampling strategy, and training dynamics. Identify recurring error patterns, trace likely root causes, and propose practical fixes.
• Computer Vision System Improvement: Use computer vision knowledge to suggest changes to the data pipeline, training setup, evaluation process, or model behavior based on findings from experiments and failure analysis.
• Python Implementation: Implement proposed changes in Python, including data processing scripts, evaluation tools, dataset filters, training configuration changes, visualization utilities, and experiment tracking improvements.
• Cross-Functional Collaboration: Work with operations and annotation teams to understand domain-specific edge cases, refine labeling guidelines, adjust processes, and document findings clearly.
• Documentation & Process: Document experiments, failure modes, decisions, and process updates so the team can reuse the workflow and build on what you learned.
  

• Computer Vision Experience: Hands-on experience with computer vision tasks such as classification and detection, including training and evaluating models on real-world image data.
• Debugging Mindset: Ability to debug model performance using targeted evaluations rather than only looking at aggregate metrics, and to trace issues through data, labels, augmentations, and training behavior.
• Proficient Programming Skills: Good Python skills and familiarity with common ML/CV libraries such as PyTorch, comfortable reading existing code and improving it incrementally.
• Communication & Collaboration: Clear communication skills and willingness to interact with operations, annotation, and QA teams to align on domain-specific edge cases and labeling guidelines.
• Documentation Discipline: Ability to document experiments, failure modes, decisions, and process updates so that findings are reusable across the team.
  

• Experiment Tracking: Familiarity with experiment tracking tools such as ClearML, Weights & Biases, or equivalents.
• Dashboards & Visualisation: Experience building dashboards, visualizations, or evaluation reports to surface failure patterns and track model behavior.
• Real-World CV Systems: Previous work on industrial, robotics, manufacturing, safety, medical, or other real-world computer vision systems.
  

• Ownership & impact: Work on hard, real-world vision problems that directly improve manufacturing for some of the world’s largest producers. Your contributions will run in factories across 15 countries.
• Growth path: Learn end-to-end applied computer vision — from data and labels through training and evaluation — by working alongside an experienced R&D team on production systems.
• Compensation: Competitive intern compensation and comprehensive support.
• Location: Modern office in the heart of Zurich; enjoy the quality of life of Switzerland and the dynamism of a high-growth startup.

If you’re excited about tracing computer vision problems end-to-end, sharpening real-world models with focused experiments, and seeing your work deployed in factories across the globe, we’d love to meet you.