# Senior Engineer - Data Recommendations at Mill

- Company: Mill
- What the company does: Mill is the smartest device in your kitchen. Mill turns would-be food waste into resources for the Earth. Keep filling it for weeks. Backed by GV.
- Company website: https://www.mill.com
- Type: Startups
- Level: Senior
- Location: San Bruno, California
- Work setup: On-site
- Pay: $210K to $240K base salary per year (USD)
- Posted: 2026-07-10
- Apply by: 2026-10-08
- Apply: https://job-boards.greenhouse.io/mill/jobs/4714076005
- Page: https://www.1752.vc/careers/jobs/mill-senior-engineer-data-recommendations/

## About the role

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 they'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

Tags: Software