Senior Machine Learning Engineer, Ads Content Understanding
$216,700–$303,400
Jul 12, 2026
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Jul 21, 2026
What this job asks for AI summary
This applied machine learning engineering role sits within Reddit's Ads Content Understanding team, which produces signals describing what Reddit content is about, its brand safety, and commercial intent. The work centers on building, deploying, and monitoring production ML systems — including NLP classifiers, LLM-based pipelines, and content taxonomies — that power contextual advertising, shopping ads, and auto-targeting. It suits an experienced engineer with a track record of shipping end-to-end ML systems at scale, ideally in content understanding or ads domains.
Senior level · 5+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
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 7,500 people nationally plausibly meet what this posting asks for (software developers). range 3,150–11,200
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.
What the occupation pays Median $138,970 (middle half $107,524–$175,762).
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 framed as 'Applied MLE' — not a research scientist or pure data science position. The primary day-to-day work is building and shipping production ML systems (models, pipelines, serving), which maps most naturally to Software Developers (15-1252); Data Scientists (15-2051) is a credible runner-up given the heavy NLP/modeling emphasis.
NLP/language model experience is listed under Required Qualifications with firm language ('Some experience building and shipping NLP / Language models…'), making it a hard gate despite the softening word 'some'.
LLMs appear in both the responsibilities and required qualifications with firm language ('Drive LLM and modern ML best practices… define when to prompt, finetune, or distill'), treating this as a required capability.
ML pipelines (offline training, feature pipelines, online serving, monitoring, experimentation) appear under Preferred Qualifications, so they are marked preferred.
PyTorch/TensorFlow, Python, Go/Java/C++, model serving, feature pipelines, model monitoring, and model distillation all appear under Preferred Qualifications and are marked preferred accordingly.
No compensation figures are stated in the posting.
The posting notes the role can be worked remotely in any country where Reddit has a physical presence; per caller instruction, this is treated as a fully-remote national (US) role.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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