The posting
Match Group AI Team Introduction
- Detailed article: Introduction to Match Group AI Team (written in Korean)
Working as a Senior MLSE at MG AI
- On-device AI Face Verification Pipeline Optimization
- 10 Python Performance Optimization Tips for High-Performance ML Backends
What You’ll Do
- Lead Projects Across Teams: Turn a broad goal into a concrete plan, and keep ML Engineers, PMs, and brand partners across our global offices (Palo Alto, LA, New York, Vancouver, Dallas, Tokyo) aligned. Clear blockers, including ones outside our team.
- Design and Build ML Systems: Design backend services and real-time/batch data pipelines that bring ML models to production, from first prototype to millions of users. Work as a real technical partner to ML Engineers.
- Serve Models Fast and at Low Cost: Serve deep learning models and large language models with low latency and reasonable GPU cost. Improve throughput with batching, caching, and better use of hardware.
- Raise the Bar: Set the example in problem definition, design docs, and AI-driven development, and help other engineers grow.
Required Qualifications
- Project Ownership (most important): A track record of leading a complex project from a rough goal to a production system you could stand behind: defining the problem, choosing the technical direction, and owning the outcome. You can explain the trade-offs behind your technical and product decisions.
- Engineering Experience: 5+ years of software engineering (backend, ML systems, data engineering, or similar), including building and running services or data pipelines in production.
- System Design: You can design scalable, reliable systems and clearly explain the trade-offs.
- Hands-on Coding With AI: You write clean, well-tested code (Python preferred), and AI coding agents are part of your daily work.
- High Agency and Grit: You find what needs to be done and drive it to a result fast, without waiting for instructions or cutting corners on quality. When you hit a wall, you find another way.
- Collaborative and Coachable: You understand what others really need and can persuade them. You take feedback well, act on it, and use AI to learn new things quickly.
- Professional Working Proficiency in English and Korean: Able to lead business meetings and take part in complex discussions without help.
Preferred Qualifications
- Have a strong base in CS fundamentals, or have worked closely with ML Engineers on how models are trained and served
- Have worked as a tech lead or manager
- Have built Trust & Safety systems, recommendation system, AI product features, or ML APIs used by multiple teams
- Have served ML models (vLLM, Triton, Ray Serve) or built large-scale backends and data pipelines (Spark, Flink, Kafka)
- Have turned vague product ideas into something users love, without every detail spelled out
- Have worked with teams in other companies, countries, or time zones
- Native-level English
Hiring Process
- Work type: Full-time
- Legal Entity: Hyperconnect / Brand: Match Group AI
- Recruitment Process: Resume Review > Technical Interview > Technical Deep-dive & Cultural Alignment Interview > Offer
- (* Please note that part of the interview process may be conducted in English)
- For the document screening stage, only successful candidates will be individually notified of the results.
- Application documents: A detailed, career-based English resume (PDF) in free format
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