---
title: 'Senior Engineer - Data Recommendations at Mill'
canonical: 'https://feeny.ai/job/senior-engineer-data-recommendations-mill-san-bruno-jgyf7peaay8d'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Engineer - Data Recommendations at Mill

- **Company:** Mill
- **Location:** San Bruno, CA
- **Posted:** 2026-07-10
- **Last confirmed live:** 2026-09-11
- **Apply:** https://job-boards.greenhouse.io/mill/jobs/4714076005

## 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.

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.

## 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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