TL;DR

Machine Learning Software Engineer, Backend (%hirify_global% Seoul): Delivering machine learning models into real-world %hirify_global% features at scale with an accent on ensuring they’re robust and performant. Focus on designing and building machine learning serving pipelines, backend services, and distributed workers.

Location: Must be based in Seoul

Company

%hirify_global% is a popular dating app that revolutionized how people meet, growing from 1 match to one billion matches in just two years.

What you will do

Design and build machine learning serving pipelines, including daily and hourly batch jobs, to deliver model outputs reliably and efficiently to production systems.
Develop and maintain backend services and distributed workers that enable ML models to be served, consumed, and monitored at scale across %hirify_global%’s products.
Collaborate closely with machine learning engineers to operationalize new models, ensuring smooth deployment, integration, and performance in production.
Partner with ML engineers and product teams on LLM-related projects, applying large language models to deliver practical, measurable impact on %hirify_global%’s key business problems.
Ensure the scalability, reliability, and robustness of ML-driven systems operating in %hirify_global%’s high-traffic production environment.

Requirements

2+ years of experience in software engineering, with a focus on backend, machine learning, or data engineering
Strong foundation in CS fundamentals, including operating systems, computer architecture, data structures, and algorithms
Experience in developing ML/AI-related services or a solid understanding of related engineering concepts
English communication skills, with the ability to lead technical discussions and collaborate effectively with U.S.-based teams
Proficiency in at least one programming language among Java, Kotlin, Golang, Python, or JavaScript (TypeScript), with the ability to quickly learn and adapt to other languages

Nice to have

Practical experience with big data or stream processing frameworks such as Spark or Flink, and familiarity with using DataBricks for data pipelines or feature stores
Familiarity with deploying applications in Kubernetes and working with cloud environments such as AWS
Familiarity with ML model serving frameworks such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray Serve

Culture & Benefits

Work hand-in-hand, building %hirify_global% for our members.
Take accountability and strive to make a positive impact in all aspects of our business, through ownership, innovation, and a commitment to excellence.
Cultivate a culture where it’s safe to take risks.
Focus on how to best move forward when faced with obstacles.
Build a workplace that reflects the rich diversity of our members by leveraging different perspectives and other ways of thinking.

Hiring process

Recruitment Process: Document Screening > Coding Test > Hiring Manager/Recruiter Call > 1st Interview > 2nd Interview > 3rd Interview > Final Acceptance
Most of the interview steps will be conducted in English

Machine Learning Software Engineer, Backend (Tinder Seoul)