Uber · Seattle, WAremote

Salary
$232,000–$258,000from the description
Posted
Jul 17, 2026
Location
Seattle, WA
Last confirmed open
Jul 21, 2026

What this job asks for AI summary

A senior individual-contributor ML engineering role focused on setting the technical strategy for foundation models that power search, recommendations, and conversational AI across ride-hailing and delivery products. The work involves driving architecture decisions for retrieval, ranking, personalization, and large language model systems at global scale, while mentoring senior engineers and shaping long-term investment choices around building, fine-tuning, or partnering on models. Suits a deep learning specialist with substantial experience in large-scale search or recommendation systems.

Staff level · 8+ years · Remote · Master's required · Full-time

Must have (10)
deep learningtransformersretrieval systemsranking systemsembeddingsPyTorchdistributed trainingLLMssearch systemsrecommendation systems
Nice to have (2)
foundation modelspersonalization

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 850 people nationally plausibly meet what this posting asks for (data scientists). range 170–1,300

Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.

What gives you an edge
transformers9%embeddings10%

Rare in this occupation — lead with these, and say what you built with them.

What won't set you apart
deep learning40%

Most people in this occupation already list these. Still required — just not what gets you shortlisted.

What the occupation pays Median $122,874 (middle half $87,544–$162,374). 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 28, 2026. It is a model, not a headcount.

Why we read it this way (8)

The role is explicitly titled 'Staff ML Engineer (IC6)', making Staff seniority unambiguous both in advertised framing and in actual scope (cross-team technical direction, long-term roadmap ownership, mentoring senior engineers).

The JD requires a Master's or Ph.D in CS, Engineering, or Mathematics with no 'or equivalent experience' escape clause — Master's is treated as the minimum hard degree gate.

SOC classification is Medium confidence: the role is primarily about building and owning large-scale ML/AI models (pointing to 15-2051 Data Scientists), but the emphasis on distributed systems engineering, architecture decisions, and production-scale infrastructure also fits 15-1252 Software Developers. 15-2051 was chosen because the core deliverable is model strategy and ML system design.

Compensation figures are location-specific (San Francisco CA, Seattle WA, Sunnyvale CA all show the same $232K–$258K/year range). The caller has declared this a fully-remote, national-pool role, so no metro is set; the stated salary bands are retained as the best available comp signal.

Search systems, recommendation systems, and conversational AI are listed as domains of required demonstrated ownership — captured as must-have skills reflecting the explicit 'Demonstrated ownership' gate in Basic Qualifications.

Foundation models and personalization appear primarily as scope/context descriptors in the role narrative rather than as explicit hard gates in the qualifications section — marked preferred accordingly.

Multi-team initiative leadership, roadmap definition, and mentorship appear under Preferred Qualifications and are not captured as named technology skills.

Caller marked this a fully-remote role — scored against the national candidate pool.

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