Staff AI Engineer at LinkedIn
Mountain View, CA
$175,000–$287,000from the description
Aug 10, 2026
Mountain View, CA
Sep 24, 2026
What this job asks for AI summary
A Staff-level individual contributor role at LinkedIn focused on owning end-to-end machine learning systems — including recommender and classification systems — that run in production at massive scale. The engineer will handle the full lifecycle from system design and model training through experimentation and GPU fleet management, while also setting technical direction across teams and mentoring other engineers. Best suited for experienced ML practitioners with a background in large-scale recommendation or ranking systems.
Staff level · 4+ years · San Jose-Sunnyvale-Santa Clara, CA · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 2 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 350 people in the San Jose-Sunnyvale-Santa Clara, CA area plausibly meet what this posting asks for (software developers). range 260–460
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 $217,796 (middle half $177,469–$231,052). 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 Aug 12, 2026. It is a model, not a headcount.
Why we read it this way (8)
The role lists three possible work locations — Sunnyvale, San Francisco, and New York City — all as hybrid. The CBSA is set to San Jose-Sunnyvale-Santa Clara (the primary LinkedIn HQ metro), but candidates in San Francisco (CBSA 41884) or New York City (CBSA 35620) are equally eligible.
The Basic Qualifications state '4+ years of industry experience in software design, development, and algorithm related solutions' and separately '4+ years experience in programming languages such as Java, Python'. Java and Python are listed as examples ('such as'), so they are treated as interchangeable options for the language requirement rather than two distinct hard gates.
The Basic Qualifications also require '4+ years experience with machine learning, data mining, and information retrieval or natural language processing' — this is captured as a role-level ML requirement. Data mining, information retrieval, and NLP are framed as alternative domains within that single requirement rather than separate skills.
A Bachelor's degree in CS or equivalent practical experience is listed as a Basic Qualification; because equivalent experience is explicitly accepted, the degree requirement is set to None.
The Preferred Qualifications call out '6+ years of relevant AI/ML experience' and an MS or PhD — both are preferred, not hard gates.
The 'Suggested Skills' section (leading engineers, strategic thinking, Big Data, GAI/LLMs) is treated as preferred/contextual rather than a hard gate, as it is a separate, aspirational section distinct from the Basic and Preferred Qualifications blocks.
SOC classification is Medium confidence: the role is primarily about building and owning ML/AI software systems (15-1252), but the heavy modeling, experimentation, and research publication emphasis creates genuine overlap with Data Scientists (15-2051).
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): AI code development.
Read the full posting
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