Data Scientist, AI/ML
Jobgether
$220,000–$290,000from the description
Jul 15, 2026
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Jul 21, 2026
What this job asks for AI summary
This role centers on building and deploying machine learning systems that analyze large-scale reliability experiment data to detect failures, identify root causes, and generate remediation recommendations for distributed software platforms. The work spans model development, data pipeline construction, and production integration, drawing on techniques such as causal inference, graph ML, time-series modeling, and reinforcement learning. It suits an experienced ML practitioner comfortable bridging research and engineering in infrastructure or reliability-oriented contexts.
Senior level · 5+ years · Remote · Full-time
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 6,900 people nationally plausibly meet what this posting asks for (data scientists). range 2,050–10,400
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 (6)
The Requirements section lists causal inference, graph ML, time-series modeling, and reinforcement learning together as a single 'hands-on experience with machine learning approaches such as…' bullet — the 'such as' qualifier means any one of these satisfies the requirement, but the capability itself is a hard gate. All four are retained as required skills with alternatives left empty because they are distinct techniques, not interchangeable substitutes for each other.
No specific ML framework or programming language (e.g. Python, PyTorch, TensorFlow) is named anywhere in the posting, which is unusual for a production ML role; no such skills were invented.
The role is posted via Jobgether on behalf of an unnamed partner company; the hiring employer's identity is not disclosed.
Equity, 401(k) matching, and flexible PTO are mentioned as benefits but no equity range is quantified.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): time-series modeling, chaos engineering.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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