Computer Vision Intern, Fall/Winter 2026

About the Role

Mill is seeking a Computer Vision Intern for Fall/Winter 2026 to gain hands-on experience applying research within a fast-moving company. This is a hybrid role based in San Bruno, CA.

Key Responsibilities

• Build and improve computer vision models (detection, segmentation, classification) for material and food recognition.
• Curate, explore, and quality assurance (QA) large image/video datasets, identifying failure modes, duplicates, and labeling issues.
• Develop and scale training pipelines and experiment-tracking/reporting tools to ensure reproducibility and easy comparison of results.
• Design and run rigorous model evaluations and contribute to progress measurement.
• Collaborate with engineering and data teams to move promising results toward production.
• Document methods and share findings with the team.

Requirements & Tech Stack

• Strong programming in Python.
• Hands-on experience with a deep-learning framework.
• Solid grounding in modern computer vision (object detection, segmentation, representation learning).
• Experience training and evaluating models on real datasets.
• Comfort with the messiness of real-world data.
• A genuine interest in translating research skills into practical, shipped systems.

Qualifications

• Currently pursuing (or recently completed) a Degree in Computer Vision, Machine Learning, Robotics, or a related field.

Nice to Have

• Experience with MLOps / experiment-tracking tooling (ClearML, Weights & Biases, MLflow).
• Experience with dataset-management and curation tooling (FiftyOne / Voxel51, CVAT, Roboflow).
• Familiarity with data/training pipelines, cloud (AWS/GCP), and Docker/Kubernetes.
• Publications or open-source contributions in CV/ML.

Logistics

• Location: San Bruno, CA — hybrid
• Duration: [e.g., 3–6 months, flexible around your academic schedule]
• Start date: immediate