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. Match Group aims to spark meaningful connections for everyone, worldwide, and the MG AI team's role is to bring cutting-edge AI to unblock the challenges along that journey, across diverse domains (e.g., Recommendation, Trust & Safety, Profile Enhancement).
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 Product Manager at MG AI
While engineers focus on building and shipping models, Product Managers at MG AI own the why and the what. We translate complex, often ambiguous business challenges from Match Group's brands into clear ML product strategy, and we drive execution across a globally distributed team. The PMs who thrive here are strategic troubleshooters with a bias for action: they spot what is blocking progress and drive it to resolution instead of waiting.
This is a communication-first role, but that does not mean coordination alone. Your core job is to figure out which problem is worth solving, articulate it in clear and precise language, and drive alignment among a diverse set of stakeholders across cultures and time zones. You own the product thinking end to end: framing the problem, shaping the plan, and defining what we build.
You will work on projects that leverage a wide range of technologies, from on-device ML modules to server-side AI models and LLMs. You do not need to be an ML expert on day one, but you must learn fast and become technically fluent enough to make sound product calls, because the technology and the problems keep changing.
What You'll Do
Frame the Problem: Figure out which problems are worth solving and why, and articulate them in clear, precise language that a diverse team can rally around.
Shape the Roadmap: Decide what matters most, sequence the work, make the tradeoffs, and write PRDs, keeping partners aligned as priorities shift.
Navigate Complex Stakeholder Maps: Act as the connective tissue between Match Group's brands, and the many functions within them, and MG AI engineering. Read the unspoken dynamics, build alignment across brands, functions, cultures, and time zones, and keep everyone moving in the same direction.
Hands-on Execution: Stay deeply involved in the details. Use experiments, behavioral data, and research to guide your calls when signals are imperfect, unblock engineering, and make the small decisions that keep a project moving.
Required Qualifications
Exceptional Communication & Stakeholder Management (most important): You excel at managing stakeholders in complex, high-ambiguity situations. You read between the lines, sense interpersonal and organizational dynamics, and build alignment across teams with competing priorities. This is the single most important quality for this role.
4-6 years of product management experience in the Tech domain, ideally on complex systems or data or ML-driven products.
Fast Learning Curve & Strong Will to Learn: You do not need to be ML-savvy today, but you must ramp quickly and become technically fluent enough to shape direction on model behavior and tradeoffs without needing to be deeply technical.
Fluent in English (Able to conduct business meetings and participate in complex discussions without requiring assistance.)
Fluent in Korean (Sophisticated professional interactions with native-level precision and an understanding of cultural nuances.) Essential for cross-functional collaboration within the Seoul office.
Strong Ownership & Bias for Action: A track record of driving problems to resolution without waiting for permission. You are comfortable operating with ambiguity and making principled calls when the signals are imperfect.
Analytical Rigor: Comfort with data. You can define metrics, design and read experiments, and let evidence guide your decisions.
Global Operational Readiness: Ability to accommodate flexible working hours for regular early morning syncs with US teams (EST/PST).
Preferred Qualifications
A Point of View on AI Tooling: A clear sense of how AI tools can raise the quality and speed of product work, and a habit of using them (e.g., Claude, ChatGPT, Cursor).
ML Product Experience: Exposure to ML-driven products (Recommendation, Search, Ranking, or Trust & Safety) and a working understanding of the ML lifecycle, from data to online A/B testing.
Matching Products Experience: Experience with products that match people or content (e.g., dating, marketplaces, social feeds, or hiring).
Internal Platform / B2B2C Experience: Success in a role where your primary customers were other internal business units or engineering teams.
Cross-functional Collaboration: Experience working with diverse, globally distributed teams and organizations.
