---
title: 'Computer Vision, Fall/Winter 2026 at Mill'
canonical: 'https://feeny.ai/job/computer-vision-fall-winter-2026-mill-san-bruno-792bavbv5g37'
type: 'job'
last_seen: '2026-09-25'
---

# Computer Vision, Fall/Winter 2026 at Mill

- **Company:** Mill
- **Location:** San Bruno, CA
- **Posted:** 2026-09-24
- **Last confirmed live:** 2026-09-25
- **Apply:** https://job-boards.greenhouse.io/mill/jobs/4737741005

## Job description

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.

## The role

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

## What you'll bring

- 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

Logistics

- 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

## About Mill

## Company Overview
- **One-liner**: Mill makes it easy to keep food out of landfills with innovative, odorless food recycling solutions for homes, workplaces, and cities.
- **Entity Type**: Private (Series C)
- **Headquarters**: San Bruno, California, USA
- **Founded**: 2020
- **Founders**: Not publicly available (founded by a team from Nest Labs / Google, though specific names are not widely publicized)

## Core Business
- Primary industry: Environmental Services / Consumer Hardware & Software
- Target customers: B2C (homeowners), B2B (grocery and food service partners via Mill Commercial)
- Mission: To eliminate waste for good, starting with the food that ends up in landfills. The goal is to turn kitchen scraps into food for chickens, keeping food in the food system and out of landfills.

## Products & Services
- **Mill Food Recycler (Home)**: An odorless, effortless food recycling bin for the home. It uses intelligent tech to dehydrate and reduce food volume by 80% overnight. Users do not need to press a button; the device senses how much is added. The resulting grounds are shipped to Mill's small-farm partners for use as chicken feed. Type: Consumer Hardware + Service (subscription).
- **Mill Commercial**: A new solution for grocery stores and food service businesses to manage food waste at scale, leveraging the same core technology. Type: B2B Hardware + Service.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Total Funding**: $170.8M across 6 rounds [linkedin.com](https://www.linkedin.com/company/mill)
- **Key Metric**: 21,000,000+ pounds of food kept out of landfills [mill.com](https://www.mill.com/)
- **Notable Investors/Partners**: Prelude Ventures (led Series C), Climate Pledge Fund (Amazon), and others [linkedin.com](https://www.linkedin.com/company/mill)
- **Growth Signals**: 110 total employees [builtin.com](https://builtin.com/company/mill) (LinkedIn reports 548, likely including contractors/partners) [linkedin.com](https://www.linkedin.com/company/mill); 14 active job postings as of mid-2026; launch of Mill Commercial; headcount growth of +0.4% monthly [linkedin.com](https://www.linkedin.com/company/mill)

## Competitive Advantages
- **Hardware + Software Moat**: The combination of a custom hardware appliance, embedded firmware, and a computer vision AI engine creates a difficult-to-replicate system.
- **Network Effect**: The more users Mill has, the more food waste is diverted, strengthening their supply chain of grounds for chicken feed and their partnerships with farms.
- **Brand & Design**: A strong focus on industrial design and user experience (odorless, effortless, beautiful) differentiates it from compost pails and garbage disposals.
- **Climate Impact**: Directly addresses methane emissions from landfills (methane is 80x more potent than CO2), giving it a strong mission-driven narrative.

## Strategic Focus
- **Scaling the Home Business**: Expanding the subscriber base for the home food recycler.
- **Launching Mill Commercial**: Entering the B2B market with grocery and food service partners to capture waste upstream.
- **International Expansion**: Likely future focus, given the global scale of food waste.

## Why Work Here
- **Mission-Driven**: Employees are directly working on climate change, keeping food out of landfills.
- **Hybrid Work**: Hybrid work environment (typical time on-site: 2 days a week) [builtin.com](https://builtin.com/company/mill).
- **Culture**: Described as a mix of hardware, software, and AI engineering with a startup feel. Offers company equity, 401(K), generous parental leave, free snacks, and company-sponsored family events [builtin.com](https://builtin.com/company/mill).
- **Engineering Focus**: Heavy investment in hardware engineering (San Bruno) and software/AI (Computer Vision). Roles include Hardware Test Engineer, Senior Firmware Engineer, AI Engineer (Computer Vision), and Product Design Engineer [greenhouse.io](https://job-boards.greenhouse.io/Mill).
- **Employee Rating**: 3.4/5.0 on LinkedIn (23 reviews), with Culture rated 3.7 and Compensation rated 3.6 [linkedin.com](https://www.linkedin.com/company/mill).

## Sources
1. [mill.com](https://www.mill.com/)
2. [greenhouse.io](https://job-boards.greenhouse.io/Mill)
3. [builtin.com](https://builtin.com/company/mill)
4. [linkedin.com](https://www.linkedin.com/company/mill)

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