Synced from Lever · Jul 27

Machine Learning Software Engineer

Match GroupSeoul, South KoreaPosted Jul 27, 2026
Machine Learning EngineerHybridMid
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Mirrored from Match Group's own Lever careers system · refreshed hourly

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Jul 27
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Lever
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Job description

Match Group AI Team Introduction

Match Group AI (MG AI) is the central tech organization that drives innovation across Match Group’s global portfolio, including Tinder, Hinge, Azar, Pairs, Match, BLK, etc. Our mission is to solve the most complex challenges in online dating (e.g., Recommendation, Trust & Safety, Profile Enhancement) by bridging cutting-edge AI research with excellent software engineering.

Unlike brand-specific teams (e.g., Tinder, HYPERCONNECT AI), MG AI team offers the unique opportunity to impact the entire Match Group ecosystem. You won't just build for one app; we aim to develop scalable AI solutions that power Tinder, Hinge, and beyond, defining the technological gold standard for the global dating industry.

 

Working as a MLSE at MG AI

While ML Engineers focus on modeling, Machine Learning Software Engineers (MLSEs) at MG AI team focus on the critical bridge between research and production. We ensure that state-of-the-art models (including LLMs and Multimodal systems) are integrated into high-traffic environments, serving millions of users in real-time.

We also upload a selection of interesting problems solved by our team's engineers to the Hyperconnect Tech blog (written in Korean).

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What applying to Match Group usually looks like

Based on publicly available information, candidates applying through lever can generally expect an online application form requesting a resume and basic details, sometimes with optional questions about experience or motivation. After submission, an initial recruiter screen may occur, followed by additional conversations with hiring managers or team members, which may include multiple stages such as technical assessments, case studies, or panel discussions depending on the role, whether at Match Group or elsewhere. Communication is typically handled through email or the Lever platform itself, and response times vary based on the volume of applicants and internal scheduling. Candidates should typically prepare standard materials like a resume and portfolio if relevant, and can commonly expect to receive status updates directly through the system, though the exact structure and pace of the process may differ by team and position.

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Machine Learning Software Engineer
Match Group · Seoul, South Korea
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