Senior Machine Learning Engineer, Menu Personalization
About The Position
We are looking for a Senior Machine Learning (ML) Engineer for the Menu Personalization team, someone who helps build and operate the recommender stack that runs in production. You will design, build, and operate ML systems across feature pipelines, training workflows, model serving, experimentation tooling, and the infrastructure underneath, owning significant parts of the stack end to end. You will be expected to bring a point of view on how we improve personalization and to back it with data and user evidence. You will partner with Data Scientists to take models from notebook to production, with Data Engineers on features and pipelines, with Backend Engineers on online inference paths, and with Product on what to build next.
Requirements
- 5+ years building and operating production ML systems.
- Production experience with recommender systems or large-scale personalization is a strong plus.
- Fluency across our data and ML stack (Python, Spark) and working knowledge of our backend and platform stack (Go, Kafka, Kubernetes), with hands-on experience across pipelines, model serving, and observability at scale.
- Statistical literacy to design honest experiments and the judgment to know when a model is actually better versus when the metrics are lying to you.
- Operational judgment to diagnose system misbehavior, find root causes, and ship systems you can debug under real load.
- Hands-on experience with AI tooling (Claude Code, Cursor, Copilot) beyond casual experimentation; you use AI agents every day and have a practical sense of how the context you provide shapes output quality.
- Product sense: opinionated about what should be built and why, with the ability to back it with evidence and translate it into business value.
- A bias to ship; you take full ownership and finish the last twenty percent.
Responsibilities
- Build and operate the ML systems behind menu personalization, working hands-on across feature pipelines, training workflows, model serving, experimentation tooling, and infrastructure.
- Take research and experiments to reliable production systems, partnering with Data Scientists on services that meet real latency, scalability, and observability requirements.
- Own significant components of the recommender stack end to end, from design through deployment and ongoing operation.
- Operate what you build, instrumenting and improving your systems in production because shipping is the beginning of the learning cycle, not the end of it.
- Contribute to the personalization roadmap with Product and Engineering, backing your point of view with data and user evidence.
- Help raise the technical bar on the team through code and design reviews, mentorship, and the example you set on production ML craft.
Benefits
- 75% discount on weekly HelloFresh and Chefs Plate meal kits
- 50% off weekly Factor meal box
- Health & Dental benefits from day 1
- A Health Spending Account
- Unlimited access to the Headspace app
- 25% discount on GoodLife fitness memberships
- Generous vacation and PTO
- A parental leave top-up program for expectant parents
- Support for career progression and continued learning through experiences and initiatives owned by our dedicated L&D team
- Team socials and engaging company days
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
