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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. As the Recommendations Engineer at Mill, you'll own the recommendation system end-to-end — from the signals and models that decide what to recommend, to the feedback loop that tells you whether it worked. You'll be part of the Data team that also manages Data Platform, Integrations and Warehouse. You'll partner with product and engineering teams to make sure recommendations are useful, accurate, and get better over time. What You'll Do Build and operate the customer-facing recommendation engine that turns food waste data into actionable recommendations — purchasing suggestions, anomaly explanations, operational nudges — including LLM-based logic where useful Build and operate the customer-facing recommendation engine that turns food waste data into actionable recommendations — purchasing suggestions, anomaly explanations, operational nudges — including LLM-based logic where useful Train, evaluate, and iterate on models for recommendation in food waste and usage data, improving accuracy over time Design the features and signals — from CV/IoT data and other sources — that feed the recommendation and detection models Define and track the metrics that measure whether recommendations are actually useful to customers, not just whether the pipeline ran successfully Bring CI/CD and experimentation discipline to model and recommendation-logic changes — automated testing, staged rollout, A/B testing or holdouts, and rollback paths Partner with the Data Platform team to define what data and signals you need, and with other engineering teams on the inputs their systems produce Continuously monitor recommendation and model performance in production, and drive the fix when it degrades What We're Looking For Have designed, built, or operated a recommendation system in production — one that combines multiple data sources into a single customer-facing output — not just contributed data to someone else's model Experience training, evaluating, and iterating on models for anomaly detection, pattern recognition, or a similar applied ML problem in production Experience building recommendation or personalization logic using LLMs (prompt-based scoring, retrieval-augmented generation, agent-based reasoning) in a live product, not just a prototype Comfortable working with production data (Python, SQL) to source and prepare inputs for your models, even if you're not the one building the underlying data platform Have brought CI/CD and experimentation discipline to model or product-logic changes (automated testing, staged rollout, rollback, A/B testing), with a track record of measuring whether a change actually improved outcomes 5 years of experience in applied ML, recommendation systems, or a closely related field A bias toward action Nice to Have Experience with anomaly/fraud detection, forecasting, or similar pattern-detection ML problems Exposure to computer vision or IoT sensor data as a model input Familiarity with feature stores or ML feature pipelines Experience with Hex, Mixpanel, Tableau, or similar BI/analytics tools The estimated base salary range for this position is $210k to $240k, 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.

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

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. As a Firmware Engineer at Mill, you’ll be working with a small dynamic team on a novel product. Your day-to-day will include hands-on work with hardware components and lab equipment as well as production code. Since we’re a small team, your work and learning will span Development, Testing, and Debug as we push towards launch. This role is for someone who wants to learn and be creatively challenged. Responsibilities Work closely with the Mill cross functional team on the embedded software and hardware validation of new products. Writing, testing, and reviewing new embedded code to run on our systems and exploring new ways to control our system. Hands-on support debugging systems during commissioning and supporting testing activities by working with electrical engineers and product designers to troubleshoot and drive system level performance. Implementing prototype drivers and testing on hardware systems. Minimum Qualifications BS, MS or PhD in Electrical Engineering, Computer Science, Computer Engineering (obtained) 1-3 years professional experience in embedded software development Ability to work 3-5 days a week in office at our San Bruno location Experience writing, testing, and debugging embedded C to control electromechanical components and read sensors Strong analytical and communication skills Preferred Qualifications Experience with embedded Linux systems: Yocto preferred Experience debugging physical hardware using oscilloscopes, network/logic analyzers Past experience developing for loadcells, DC motors, PID controllers, DC fans Experience with python scripting Experience with Hardware-in-the-Loop testing platforms Experience working with CI/CD pipelines for production code The estimated base salary range for this position is $185K-210K, 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. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.

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. About the Role We're looking for a Program Manager to be the air traffic control for the Mill Commercial software platform. This is both a strategic and execution-oriented role: you'll keep multiple software teams (Fleet Management, UI, Data Integrations) moving in sync, make sure resources are deployed against the right priorities, and be the key point of contact for partners and customers whose data integrations are critical to our product. As requirements and timelines shift, you'll continually re-evaluate priorities and communicate issues or opportunities at the executive level fast. This is a fast-paced, complex organizational role built for a detail-oriented leader who thrives on bringing clarity to ambiguity. What You'll Do Track resourcing across SW teams and applications on the Mill Commercial platform, and flag gaps or conflicts before they become blockers Serve as Scrum Master and Jira lead for the SW Applications & Data team Own key third-party data integrations, customers, partners, and vendors, including sample data requests, schema, and API connections Build and maintain the integrated SW deployment schedule across Fleet Management, UI Design, and Data Integrations Run regular executive updates on resourcing, scheduling, and budget Turn shifting requirements into a shared set of priorities that eng, product, and partners can plan against Surface risks, blockers, and scope creep the moment you see them, with enough context for execs to make a fast call Map dependencies across teams (SW, firmware, data, CV) to catch where one team's slip becomes another's blocker What We're Looking For 8+ years of SW program management, with strong preference for SW products with a physical hardware component Gen 1 software product experience: you've organized the development of complex, first-generation software products Software and firmware knowledge: you've worked with both on-device software and cloud-based applications for monitoring and controlling devices Data integration expertise: from native APIs to flat-file ingestion; experience with AI-powered workflows is a plus Strong cross-functional executor: you keep eng, product, ops, and sales coordinated, and you run meetings that produce clear decisions and owners Technical depth: comfortable in a room full of engineers, you can engage substantively on tradeoffs and know when to escalate Shipped multiple software products: you've taken more than one through late-stage development, pilot, and into commercial deployment Clear, direct communicator: you write status updates and requirements that get read, not skimmed, and you can distill a messy technical problem into a one-line ask for an exec or a one-page brief for a partner Fluent with AI tools: you use AI-powered tools day to day for things like summarizing meetings, drafting requirements or specs, or synthesizing data, and you can help the team find similar leverage in their own workflows Advanced with program management tools like Jira, Notion, etc., with experience running Scrum rituals up to and including Scrum of Scrums Experience coordinating dependencies across many engineering disciplines, from full stack to computer vision to data integration The estimated base salary range for this position is $185k to $210k, 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.

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. As a Firmware Engineering intern at Mill, you’ll be working with a tight-knit, fast-paced team on a novel consumer product. Your day-to-day will include hands-on work with hardware components and lab equipment as well as production code. Since we’re a small team, your work and learning will span Development, Testing, and Debug as we push towards launch. This internship is for someone who wants to learn and be creatively challenged. Responsibilities Work closely with the Mill cross functional team on the embedded software and hardware validation of new products. Writing, editing and drafting new embedded code to run on our systems and exploring new ways to control our system. Hands-on support debugging systems during commissioning and supporting testing activities by working with electrical engineers, and product designers to troubleshoot and drive system level performance. Implementing prototype drivers and testing on hardware systems. Minimum Qualifications BS, MS or PhD in Electrical Engineering, Computer Science, Computer Engineering (obtained). Ability to work 5 days a week in office at our San Bruno location Experience writing and testing embedded C to control electromechanical components and read sensors Strong analytical and communication skills. Preferred Qualifications Experience with embedded linux systems: yocto preferred Experience debugging physical hardware using oscilloscopes, network/logic analyzers Past experience developing for loadcells, DC motors, PID controllers, DC fans Experience with python scripting preferred. Experience working with CI/CD pipelines for production code. 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 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. About the Role 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. 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. What You'll Do 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. Optimize edge models for production performance, and operationalize and scale the ML pipeline with model lineage tracking end to end. Create and curate datasets per customer/vertical — more customized, purpose-driven data — to support accuracy targets across food types, kitchen environments, and deployment configurations. 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. Build annotation tooling and ground-truth generation workflows, including foundation-model-assisted labeling, to keep pace with model iteration. Bring a methodical approach and strong opinions, backed by experience, to the modeling and evaluation decisions you own — and partner with the team's MLOps and edge engineers on training practices, versioning, and deployment tradeoffs as they come up. What We're Looking For Strong fundamentals in computer vision and deep learning — segmentation, detection, classification, tracking — deep enough to make informed architecture calls. Fluency with modern ML approaches — VLMs, LLMs, foundation models, and agentic systems — alongside classical deep learning. You know when to fine-tune a ConvNet, when to prompt a VLM, and when to wire up an agent, and you understand the practical realities of putting any of them into a product. Experience evaluating ML models rigorously — designing metrics, building eval harnesses, and using results to drive product decisions rather than just publish a number. Product shipping experience — you've taken a model to production and dealt with what comes after (drift, edge cases, latency budgets), not just to a benchmark. Bias for action — you'd rather ship a good-enough experiment and learn from it than wait for the perfect plan. Experience making build-vs-buy or tooling decisions backed by data or a clear rubric, not just instinct — you can show your work on how you got there. Clear, direct communication — you can explain tradeoffs to non-technical stakeholders, push back honestly when you disagree, and write docs that others can follow. Genuine interest in applying AI to food waste reduction and sustainability. This is a mission-driven product and we want people who care about the mission. Software skills: Python, PyTorch, OpenCV. Experience with LLM and agent frameworks. Nice to Have Experience with video understanding (temporal consistency, tracking, video segmentation) Experience with MLOps tooling (Weights & Biases, MLflow, SageMaker, ClearML, or equivalents) Hardware / IoT product experience, particularly with computer vision and cameras for embedded systems The estimated base salary range for this position is $220-250K, 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. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.