ML Software Engineer, ETA at Lyft
San Francisco, CA
$140,800–$176,000from the description
Jul 19, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
This role sits on the team responsible for predicting arrival times across Lyft's ride platform, where accuracy, low latency, and reliability are central concerns. Day-to-day work spans exploratory data analysis, building and shipping statistical or ML models, and writing production-grade code that handles millions of requests. The stack includes AWS, Kubernetes, Go, Spark, Python, and Apache Airflow, and the role suits engineers with at least three years of applied ML experience.
Mid level · 3+ years · San Francisco-Oakland-Hayward, CA · Full-time
Posted 3 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 130 people in the San Francisco-Oakland-Hayward, CA area plausibly meet what this posting asks for (data scientists). range 100–170
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $173,851 (middle half $133,298–$217,653). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (6)
The role is a hybrid ML/software engineering position — the team builds production ML systems for ETA prediction at scale, making it genuinely ambiguous between Data Scientists (15-2051) and Software Developers (15-1252). The ML modeling emphasis and quantitative-field degree framing tipped the classification toward 15-2051.
AWS, Kubernetes, Go, and Python are listed as the team's technology stack in a narrative 'Our technology stack' sentence rather than under a formal requirements heading. They are marked required because the JD frames them as the production environment candidates will work in daily and the role explicitly requires writing production-quality code in that stack.
Apache Airflow and Spark appear only under the 'Nice-to-have' section and are marked preferred accordingly.
The degree requirement (B.S./M.S./Ph.D.) is explicitly paired with 'or related work experience,' so no minimum degree is hard-gated.
Compensation range of $140,800–$176,000/year is stated for the San Francisco area only; the recruiter may share different ranges for other locations.
The role is hybrid (3 days/week in-office); it is not fully remote.
Read the full posting
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