Senior Machine Learning Software Engineer, Backend (Tinder Seoul)

-Legal Entity: Hyperconnect-Brand: Tinder-Affiliation: Tinder ML Seoul TeamTeam IntroductionThe Tinder ML team drives impact across nearly every core domain of the product — from Recommendations and Trust & Safety to Profile, Growth, and Revenue optimization. Our mission is to apply machine learning to enhance user experiences, foster trust, and accelerate business growth across Tinder’s ecosystem.ML team at Tinder is organized into three groups with different roles:- Machine Learning Engineers who focus on modeling and algorithmic innovation.- Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training, serving, and feature management.- Machine Learning Software Engineers (this role) who bridge the gap between research and production — delivering machine learning models into real-world Tinder features at scale.This team plays a critical role in taking models from experimentation to production, ensuring they’re robust, performant, and impactful. Our work directly translates into measurable business outcomes — many of our models are already embedded in core Tinder user flows, influencing millions of daily interactions in real time.This team collaborates closely with ML engineers, ML infra engineers teams across the U.S. and Seoul to design and develop systems optimized for scalability and reliability in high-traffic environments. This role plays a role at the intersection of ML and software engineering — ensuring that machine learning models are effectively integrated into real-world products.ResponsibilitiesProvide technical leadership within the ML software engineering team in Seoul — mentoring peers, setting engineering best practices, and driving projects from design to production deliveryDesign and build machine learning serving pipelines, including daily and hourly batch jobs, to deliver model outputs reliably and efficiently to production systemsDevelop and maintain backend services and distributed workers that enable ML models to be served, consumed, and monitored at scale across Tinder’s productsCollaborate closely with machine learning engineers to operationalize new models, ensuring smooth deployment, integration, and performance in productionPartner with ML engineers and product teams on LLM-related projects, applying large language models to deliver practical, measurable impact on Tinder’s key business problemsTake ownership of the software engineering components of the ML production stack, including orchestration, APIs, data pipelines, model versioning, and monitoring systemsEnsure the scalability, reliability, and robustness of ML-driven systems operating in Tinder’s high-traffic production environmentWork closely with cross-functional partners — including ML Engineers, ML Infrastructure Engineers, Backend Engineers, and CloudOps teams in the U.S. — to design and ship end-to-end ML solutions, requiring effective communication and collaboration in EnglishDeliver tangible business impact by integrating machine learning models into real-world Tinder features that improve user experience, trust, and engagementQualifications5+ years of experience in software engineering, with a focus on backend, machine learning, or data engineeringStrong foundation in CS fundamentals, including operating systems, computer architecture, data structures, and algorithmsExperience in developing ML/AI-related services or a solid understanding of related engineering conceptsEnglish communication skills, with the ability to lead technical discussions and collaborate effectively with U.S.-based teamsExperience integrating and operating systems such as RDB, Redis, and KafkaHands-on experience using big data batch and stream processing frameworks such as Spark or FlinkHands-on experience using DataBricks for data pipeline or feature store Hands-on experience deploying and managing applications in Kubernetes environmentsExperience operating infrastructure on AWSProficiency in at least one programming language among Java, Kotlin, Golang, Python, or JavaScript (TypeScript), with the ability to quickly learn and adapt to other languagesSelf-motivated and proactive in taking ownership of tasks and driving them to completionPreferred QualificationsFamiliarity with ML model serving frameworks such as TensorFlow Serving, TorchServe, Triton Inference Server, or Ray ServeExperience with feature store systems and ML data pipelines supporting online/offline feature parityPractical experience building and optimizing data pipelines using modern orchestration frameworks (Airflow)Understanding of MLOps best practices including CI/CD for ML, model versioning, and automated evaluation or rollback strategiesExperience with observability and monitoring tools for ML production systems (e.g., Prometheus, Grafana)Exposure to large language models (LLMs) and familiarity with deploying or fine-tuning them for applied use casesExperience working in cross-functional global teams, effectively collaborating across time zones and disciplinesStrong understanding of machine learning algorithms and a genuine interest in applying them to production systemsRecruitment ProcessEmployment Type: Full-timeRecruitment 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)For document screening, only successful applicants will be notified individuallyApplication Documents: Detailed career-based English resume (PDF) in free format#tinder제출해 주신 내용 중 허위 사실이 있거나 관련법 상 근로제공에 결격사유가 있는 경우 채용이 취소될 수 있으며, 필요시 사전에 안내된 채용 절차 외에도 추가 전형 및 서류 확인이 진행될 수 있습니다.국가보훈대상자는 관계 법령에 따라 우대하오니, 해당되시는 분께서는 지원 시 고지해주시고 채용 시 증빙서류를 제출해주시기 바랍니다.하이퍼커넥트가 채용하는 포지션에 지원하는 경우, 개인정보 처리에 관하여서는 본 개인정보처리방침이 적용됩니다: https://career.hyperconnect.com/privacy#HPCNT