Research Engineer, Monetization AI at Meta
Seattle, WA
$183,997–$257,000from the description
Jul 17, 2026
Seattle, WA
Jul 21, 2026
What this job asks for AI summary
A research engineering role focused on building and improving large-scale machine learning systems for advertising ranking and recommendations. Day-to-day work spans designing model architectures, training pipelines, and sequence learning methods, as well as tackling data challenges through techniques like self-supervised learning and generative modeling. Best suited to ML practitioners with hands-on experience taking models from research through to production impact.
Senior level · San Francisco-Oakland-Berkeley, CA · Bachelor's required · Full-time
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 30 people in the San Francisco-Oakland-Berkeley, CA area plausibly meet what this posting asks for (data scientists). range 20–45
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 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
The job title is 'Research Engineer, Monetization AI' with no explicit seniority level in the title; advertised seniority is treated as Unspecified. However, the scope — end-to-end model development at scale, cross-functional collaboration, and SOTA research — supports a Senior classification.
The role is genuinely ambiguous between Data Scientists (15-2051) and Software Developers (15-1252): it combines ML research (modeling, publications, RecSys) with production engineering (pipelines, large-scale software architecture, deployment). 15-2051 is chosen as primary given the strong research framing and ML/RecSys focus.
Location is not explicitly stated in the posting; Meta's Monetization AI org is primarily based in the San Francisco Bay Area (Menlo Park/Meta HQ), so that CBSA is used as the best inference.
The minimum qualification requires a Bachelor's degree OR equivalent practical experience. Because the JD explicitly offers an experience-based alternative, the degree requirement is set to Bachelors (the stated minimum formal degree) — note that equivalent experience is accepted.
A PhD in AI/CS/Data Science is listed under Preferred Qualifications, as is a Master's degree — neither is a hard gate.
Skills such as semi/self-supervised learning, debiasing, domain adaptation, continual learning, cold-start, content understanding, sampling, and agent orchestration appear in the JD but are framed as domain knowledge areas rather than named, discrete tools or frameworks, so they are omitted per extraction rules.
First-author publications at peer-reviewed AI conferences (NeurIPS, ICML, ICLR, etc.) are listed under Preferred Qualifications — not a hard gate.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): large-scale ML model development.
Read the full posting
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