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Senior Machine Learning Engineer

Match Group · Hybrid

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MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last seen by MeritLog August 17, 2026Source: LeverSource version: lever-postings-v1

Source: the employer's Lever job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
Vancouver, British Columbia
Occupation
Computer Systems Engineers/Architects(O*NET 15-1299.08)

Job description

Know where you belong! Match Group is a leading provider of dating products across the globe. Our portfolio includes Tinder, Hinge, Match, Meetic, PlentyOfFish, OkCupid, The League, HER, and others, each designed to spark meaningful connections for singles worldwide. Creating a sense of belonging doesn’t stop at our products - it’s the foundation of every team we hire.   When it comes to dating, the connection starts online, but the real magic happens once you meet in real life (IRL).  We think the same is true for creating the best platforms, so we work together IRL 3 days/week. Everyone and Everywhere (E&E) is one of the world's leading online dating groups, comprising a large and prestigious dating portfolio (OkCupid, Match.com, Meetic, PlentyOfFish, Affinity, …)with millions of daily active members. We are based in Vancouver with a strong worldwide collaboration with other brands within the Match Group (NASDAQ: MTCH) such as Tinder and Hinge.   As a Senior Machine Learning Engineer, you will work as part of our ML/AI Squad, working across the organization on strategic and challenging projects to support E&E companies to achieve their business objectives. Working alongside Data Scientists, Data Engineers, BI Architects, and Product Managers, you will lead the next generation of ML/AI agent and Agentic-based solutions that will have a direct positive impact on our millions of daily users. Additionally, you will be solving complex problems that keep us awake at night, such as how to keep winning the war on Fraud, how to improve our matching algorithms and search, and how to get a fundamental understanding of what makes our users happy and successful.

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