Senior Machine Learning Engineer at Match Group
Vancouver, WA
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Jul 26, 2026
Vancouver, WA
Jul 28, 2026
What this job asks for AI summary
A Senior Machine Learning Engineer role embedded in the ML/AI Squad at Match Group's Everyone & Everywhere division (OkCupid, Match.com, Meetic, PlentyOfFish), based in Vancouver with a hybrid in-office requirement. The role centers on designing, building, and productionizing ML/AI systems — including LLM-based and agentic solutions — to improve fraud detection, matching algorithms, and user experience for millions of daily active members. Candidates should have a strong background in both ML engineering and production deployment.
Senior level · 5+ years · Vancouver, BC · Bachelor's required · Full-time
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How this req sits in the market our data
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).
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 role is based in Vancouver, BC, Canada — US compensation benchmarks do not apply.
The SOC classification is a close call: the role blends ML engineering (productionizing models, pipelines, infrastructure) with data science (deep learning, statistical modeling, algorithm development). 15-2051 was chosen because the posting explicitly names Data Scientist as an equivalent background and emphasizes statistical/mathematical depth; 15-1252 is a strong runner-up given the production engineering emphasis.
Degree requirement: the posting lists B.S., M.S., or PhD in computer science (or a scientific discipline with substantial engineering experience) as a requirement. Because a B.S. is the minimum stated degree and no equivalent-experience substitution is offered, the degree requirement is set to Bachelors.
The 5+ years figure is the stated overall experience minimum; the 3+ years for ML pipelines and LLM deployment are technology-specific and captured on those skills.
GCP is listed in the requirements section but framed as 'or other cloud providers,' making it a preferred/interchangeable skill rather than a hard gate on GCP specifically — treated as preferred with common alternatives noted.
No compensation figures are provided in the posting.
Read the full posting
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