Seoul, South Korea
Open 3 months, first seen by us 101 days agoWork setup in the employer’s posting: hybridFrom the employer’s posting
Employment type Full-time
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design backend services and distributed systems to serve, scale and monitor ML models
Build real-time and batch ML serving pipelines with low latency and high reliability
Improve retrieval, ranking and utility models for personalized recommendations
Collaborate technically with engineering teams at Tinder, Hinge, Match, Azar, Pairs and others
Design and develop backend services and distributed systems that enable the seamless consumption, scaling, and monitoring of ML models.
Design and develop ML serving pipelines (real-time and batch) to deliver model outputs with low latency and high reliability.
Improve the AI-powered personalized recommendation system to help users find better matches on Match Group’s dating apps (serve better retrieval/ranking/utility models, add better features, etc).
Engage in deep technical collaboration with engineering counterparts (Tinder, Hinge, Match, Azar, Pairs, etc.)
Open 3 monthsWe first saw this posting 101 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 101
Up longer than most. Similar jobs usually come down between day 6 and day 70.
Well past Match Group’s usual: its jobs come down by about day 43.
From 4,459 similar postings that came down, and 15 of Match Group’s. Coming down is not always a hire.
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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.
- On-device AI Face Verification Pipeline Optimization - 10 Python Performance Optimization Tips for High-Performance ML Backends What You’ll Do
- 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.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
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).
Full-time
Selected passages from the saved posting. Check the full description for conditions and exceptions.
No pay amount identified in the saved description.
Seoul, South Korea
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.
