Sr. Machine Learning Engineer at PayPal
San Jose, CA
$193,978–$246,000from the description
Jul 16, 2026
San Jose, CA
Jul 21, 2026
What this job asks for AI summary
A senior machine learning engineering role focused on designing and building ML models and AI agents for fraud prevention and other business applications. The work spans the full lifecycle — from data preparation and model development through deployment into production systems — with particular emphasis on large language models, agentic frameworks, and MLOps. Suits engineers with hands-on experience in LLM fine-tuning, distributed training, and production-grade ML infrastructure.
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 550 people nationally plausibly meet what this posting asks for (data scientists). range 330–1,200
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.
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 (10)
The posting is located in San Jose, CA with partial telecommuting permitted; the caller has overridden this to fully remote with a national candidate pool, so no metro is set.
Degree requirement is marked None because the JD explicitly accepts a Bachelor's plus 5 years OR a Master's plus 3 years — equivalent experience substitutes for the higher degree, so no single minimum degree is hard-gated.
The overall years minimum is set to 5, reflecting the lower of the two stated experience thresholds (Bachelor's + 5 years path).
The role sits at the boundary between Data Scientists (15-2051) and Software Developers (15-1252): it involves substantial ML modeling, LLM fine-tuning, and experimentation (pointing to 15-2051) but also heavy production engineering, MLOps, and agent framework development (pointing to 15-1252). 15-2051 is chosen as primary given the explicit ML Engineer title and the centrality of model design, evaluation, and LLM work.
All ten Special Skill Requirements are listed under a hard 'Minimum Requirements' / 'Special Skill Requirements' section and are treated as required. Per-skill year minimums stated in parentheses are captured in the years demanded where applicable.
DeepSpeed is listed as the primary distributed training library with Accelerate and FSDP as named alternatives in the same requirement.
vLLM is listed as the primary inference/serving framework with Ray Serve and Triton as named alternatives (Cosmos also named but is less commonly used as a direct substitute).
CrewAI is listed as the primary agentic framework with AutoGen, LangGraph, and ReAct as named alternatives.
The compensation range ($193,978–$246,000/year) is stated as specific to the San Jose, CA location; actual pay for a remote hire may differ per the posting's own language.
Caller marked this a fully-remote role — scored against the national candidate pool.
Read the full posting
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