Staff Machine Learning Engineer

About the jobThis is a job that Navii, our AI Recruiter, is recruiting for on behalf of one of our customers. Navii helps the hiring team learn more about the candidates beyond the resume. You can speak with Navii here about the role. About the roleEvery workout iFIT recommends is a small promise: that we know what a member is training for, and what they are ready for next. Keeping that promise across millions of members and every surface in the product is the job.We are hiring a Staff ML Engineer to own recommendations and search end to end, from strategy through production. You will shape how personalization works here rather than implement someone else's spec. What you will ownThe recommendation and search strategy across product surfaces: the approach, what gets prioritized, and the decisions that follow from resultsEnd-to-end ML systems for ranking, retrieval and personalization, covering data pipelines, feature design, training, evaluation and servingAn experimentation loop rigorous enough that relevance work turns into measured member impactReliability and safe iteration as the system grows, working closely with Data and SecurityThe long-term health of what you build. Projects here are not handed off to a maintenance team What we are looking forRecommendation or search systems you have taken to production and owned, not research prototypesStrong ML engineering fundamentals across ranking and retrieval: feature engineering, model training, evaluation, and the practical realities of deploymentA track record of connecting model changes to product outcomes, through experiments that informed real decisionsSolid software engineering: reliable services and pipelines, maintainable code, and comfort debugging systems you did not writeClear communication with product and engineering partners about trade-offs and progressProficiency with Claude Code as a daily working tool Even better if you haveLarge-scale personalization experience across multiple surfaces, high traffic, and catalogs that change constantlyWorked with LLMs in retrieval or ranking, or built AI-native development workflows How we workRoughly 95% of the code in our platform org is AI-generated. That has genuinely changed what engineering looks like here. We review plans before code. We build harnesses and quality gates instead of reading every diff. We invest in the workflows that make the next feature faster, and we expect engineers to own what they ship regardless of what wrote the first draft.If you already work this way, you will feel at home immediately. If you want to, this is a good place to learn it properly. Your first 90 daysBuild an end-to-end picture of how personalization and search data flows, where the key metrics live, and what the current system is actually optimizing forIdentify the highest-leverage relevance opportunities and propose an experimentation plan with clear decision criteriaShip at least one meaningful production improvement and communicate what it movedPut guardrails around reliability and data constraints so the system can keep iterating safely Compensation$175,000 to $220,000 base salary, plus a 15% target bonus. Fully remote within the United States. A note on backgroundsIf you have built and scaled recommendation or search systems anywhere, whether at a startup, a large company, or in open source, we would like to hear from you, whether or not your title has said "Staff" before. iFIT is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. How to ApplyInterested? You’ll start with a conversation with Navii, our hiring team’s AI—it's a chance for us to learn about you beyond your resume.