Software Engineer, AI/Computer Vision

<div class="content-intro"><p><span style="font-weight: 400;">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.</span></p></div><h2><strong>About the Role</strong></h2> <p>We're hiring a Computer Vision Engineer to work on the CV technology behind Mill Commercial — the computer vision and agentic systems that turn a stream of food waste into operational intelligence for commercial kitchens. Mill Commercial integrates a camera into our high-capacity food recycler; models identify and quantify food scraps, and our pipeline turns that signal into procurement and operational guidance for large food service operators.</p> <p>&nbsp;</p> <p>You'll join a small, capable team, owning the modeling and training infrastructure that powers our CV technology. You will design the cloud-side evaluation harness to determine if edge models meet production targets and build the ground-truth workflows to support them. This is a hands-on IC role for someone who brings deep computer vision fundamentals to fine-tuning models, building MLOps pipelines, and establishing a methodical approach to managing system complexity.</p> <h2><strong>What You'll Do</strong></h2> <ul> <li>Train and evaluate segmentation, classification, and mass-estimation models for the Mill Commercial camera pipeline — from prompting foundation models to fine-tuning ConvNets and VLMs.</li> <li>Optimize edge models for production performance, and operationalize and scale the ML pipeline with model lineage tracking end to end.</li> <li>Create and curate datasets per customer/vertical — more customized, purpose-driven data — to support accuracy targets across food types, kitchen environments, and deployment configurations.</li> <li>Analyze failure cases systematically — unfamiliar food classes, novel kitchen environments, challenging lighting and clutter conditions — and drive the data and modeling decisions that close accuracy gaps.</li> <li>Build annotation tooling and ground-truth generation workflows, including foundation-model-assisted labelin