Machine Learning Engineer Technical Fellow
Indeed
$227,000–$474,000from the description
Jun 30, 2026
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Jul 21, 2026
What this job asks for AI summary
A senior individual-contributor machine learning role focused on shaping the architecture and long-term strategy of search, recommendations, retrieval, and ranking systems across multiple teams. The work spans hands-on technical contributions — including generative retrieval, classification, and semantic ranking — alongside cross-team influence, mentoring ML engineers, and partnering with leadership on platform-wide initiatives. Suited to a deeply experienced ML engineer comfortable operating across organizational boundaries.
Principal level · 15+ years · Remote · Bachelor's required · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 8 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 810 people nationally plausibly meet what this posting asks for (data scientists). range 480–1,750
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
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 (9)
The title 'Machine Learning Engineering Fellow' maps to a Principal-level individual contributor: the JD describes org-wide technical authority, cross-team architectural leadership, and mentoring of other ML engineers — but no direct people management (no hiring, no budget ownership), so 11-3021 was not used.
SOC is Medium confidence: the role is a genuine hybrid of ML research/modeling (15-2051) and large-scale backend software engineering (15-1252). The emphasis on model architecture, generative retrieval, and semantic ranking tips it toward 15-2051, but the explicit backend coding requirement (Java/C/C++/Go) makes 15-1252 a credible runner-up.
The compensation range spans four geographic pay tiers ($227K–$341K at Tier 1 up to $316K–$474K at Tier 5). The min/max reported here represent the absolute floor and ceiling across all tiers; actual offer depends on candidate location.
Experience requirement is tiered by degree: 15 years with a Bachelor's, 12 years with a Master's, or 8 years with a PhD. The overall years minimum is set to 15 (the Bachelor's floor); candidates with advanced degrees qualify at lower experience thresholds.
Backend language requirement (Java, C, C++, or Go) is listed as a single interchangeable gate; Java is used as the primary name with the others in alternatives. Similarly, TensorFlow/PyTorch/SageMaker are interchangeable ML platform options.
Python and R are listed as interchangeable for data analytics; Python is the primary name with R in alternatives.
SQL database tools (Presto, AWS Athena, Postgres, BigQuery) are listed as interchangeable equivalents; Presto is used as the primary with the others in alternatives.
'Generative retrieval' and 'ranking systems' appear in the narrative/opportunity framing sections rather than the formal requirements block, so they are marked preferred.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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