Machine Learning Software Engineer (Match Group AI)

What You’ll Do

• Bridge Research to Production: Operationalize complex ML models into robust, scalable features for global brands like Tinder and Hinge.
• Build ML Services: Design and develop backend services and distributed systems that enable the seamless consumption, scaling, and monitoring of ML models.
• Build ML Pipelines: Design and develop ML serving pipelines (real-time and batch) to deliver model outputs with low latency and high reliability.
• Drive LLM Innovation: Partner with ML engineers to deploy and optimize Large Language Models (LLMs) for practical, high-impact use cases such as profile assistance.
• Co-Engineering with Brands: Engage in deep technical collaboration with engineering counterparts (Tinder, Hinge, Azar, Pairs, etc.) across various global offices, including Seoul, Palo Alto, LA, Vancouver, Dallas, and Tokyo.

Required Qualifications

• 2+ years of experience in software engineering, with a focus on Backend, ML Engineering, or Data Engineering.
• Strong understanding of CS Fundamentals (data structures, algorithms, operating systems) and distributed system design.
• Proficiency in at least one modern programming language (e.g., Python, Go, Java, Kotlin, C#) and a "polyglot mindset" to adapt to new stacks quickly.
• A strong interest in how ML models are built and a passion for solving the engineering challenges of deploying them in the real world.
• Proficiency in leveraging AI-powered tools (e.g., Claude Code, Codex, Cursor) to accelerate productivity.
• Professional working proficiency 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.

Preferred Qualifications

• Experience with the full ML lifecycle, from model training to production deployment.
• Experience in developing scalable backend servers (handling millions of users).
• Experience in developing and serving ML-driven services using frameworks such as vLLM, Triton, Ray Serve, or Seldon.
• Experience with big data or stream processing frameworks (e.g., Spark, Flink, Kafka) for building robust ML data pipelines.
• Experience in collaborating with cross-functional teams and diverse organizations.
• Fluent in English (Sophisticated professional interactions with native-level precision and an understanding of cultural nuances.)