_0.png)
Computer Vision Intern developing detection, segmentation, and classification models for food and material recognition. Responsibilities include curating and QAing image/video datasets, building reproducible training and experiment-tracking pipelines, evaluating models, documenting findings, and collaborating with engineering and data teams to deploy computer vision systems to production devices.
Mill is a waste prevention technology company reimagining what it means to eliminate waste, starting with food. We build smart systems and infrastructure for homes, businesses, and municipalities that transform food scraps from landfill-bound waste into valuable resources, including chicken feed. Tens of thousands of Mill’s residential food recyclers are already helping households divert millions of pounds of food scraps every year, paving the way for our upcoming launch of Mill Commercial—the industry’s first end-to-end solution for managing, understanding, and preventing food waste in commercial environments (e.g. grocery, restaurants, food services). At Mill, we are passionate about building easy-to-use, beautifully designed technologies that keep food in the food system and out of landfills.
We're looking for a candidate who wants hands-on experience applying their research inside a fast-moving company. As a Computer Vision Intern, you'll work directly with Mill's Computer Vision team on real production problems — from dataset curation and model training to the pipelines and experiment tooling that make our CV systems reproducible and fast to iterate on.
You'll be mentored by senior members of our Computer Vision team and see your work reach real devices and users. This is a hybrid role based in San Bruno, CA.
What you'll work on- Build and improve computer vision models — detection, segmentation, and classification — for material and food recognition and related tasks
- Curate, explore, and QA large image/video datasets, surfacing failure modes, duplicates, and labeling issues
- Develop and scale training pipelines and experiment-tracking/reporting so experiments are reproducible and results are easy to compare — i.e., help build the "experiment harness" the team relies on
- Design and run rigorous model evaluations and contribute to how we measure progress
- Collaborate with engineering and data teams to move promising results toward production
- Document your methods and share findings with the team
- Currently pursuing (or recently completed) a Degree in Computer Vision, Machine Learning, Robotics or a related field
- Strong programming in Python and hands-on experience with a deep-learning framework
- Solid grounding in modern computer vision (object detection, segmentation, representation learning, etc.)
- Experience training and evaluating models on real datasets, and comfort with the messiness of real-world data
- A genuine interest in translating research skills into practical, shipped systems
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
- Location: San Bruno, CA — hybrid
- Duration: [e.g., 3–6 months, flexible around your academic schedule]
- Start date: immediate
The estimated base hourly range for this position is $35 to $45, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor an employment visa for this role
Mill San Bruno, California, USA Office
1099 Sneath Lane, San Bruno, CA, United States, 94066
Similar Jobs
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
Designs, integrates, tests, debugs, and leads development of embedded flight software for satellite and payload systems. Responsibilities include software-hardware integration, requirements analysis, cyber vulnerability analysis, cyber monitoring algorithms, configuration automation, documentation, quality assurance, and delivery coordination. The role interfaces with multidisciplinary engineering teams and supports safety, security, and performance objectives for commercial and government space programs.
Top Skills:
BitbucketCC++ConfluenceCyber Monitoring AlgorithmsDevOpsEmbedded SystemsGitlabJavaJIRAPythonReal-Time SoftwareWireshark
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
Leads electrophysics and radar engineering for air and space payloads across the product lifecycle. Responsibilities include radar performance and trade studies, signal and image processing, RWR integration, mission design, payload effectiveness analysis, technical leadership of teams and subcontractors, anomaly resolution, and capability roadmap development. The role requires advanced radar or signal-intelligence expertise, systems integration experience, and active Top Secret/SCI clearance.
Top Skills:
Image ProcessingMatlabRadar SystemsRadar Warning Receivers (Rwr)Rf SystemsRfi MitigationSignal ProcessingStkSynthetic Aperture Radar (Sar)
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
Design and validate ASIC and mixed-signal subsystem architectures for space-based digital communication systems. Responsibilities include requirements derivation, verification planning, ADC/DAC performance analysis, technical trade studies, supplier coordination, hardware and software integration, qualification, unit sell-off, and risk mitigation. The role supports the full subsystem lifecycle and requires collaboration across engineering, program management, suppliers, and customers.
Top Skills:
AdcAsicCDacI2CJesdJtagMatlabPythonSerdesSpiVlsi
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
