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Leads the Data Platform team at Toss, building and operating scalable data pipelines and distributed systems (Hadoop, Kafka, Spark, Flink) to power real-time analytics and services for Korea’s leading fintech app.
Owns AI-driven features at Toss, defining how ML models power recommendations, search, and personalization, and measuring their business impact through experiments.
Designs, builds, and operates GPU infrastructure for AI/ML workloads, including bare-metal clusters, networking, and monitoring.
Owns the AI-driven investment content journey for Toss Securities, from content creation to user discovery and retention, using data and experiments to build trust in AI recommendations.
Data Analyst at Toss Securities responsible for quantifying product goals, uncovering problems from data, and designing metrics frameworks to align cross-team decisions in a fintech environment.
브라질 현지 근무 포지션입니다. This role is based in São Paulo , Brazil. About the Team You’ll Join Toss is South Korea's leading financial super app, trusted by over 20 million users and backed by a fully licensed financial…
Build ML models for credit risk, loan needs, and card approvals within Toss’s financial marketplace, using Python/SQL and deep learning to tailor user services.
Build and refine AI agents that converse naturally with customers via text, images, and real-time voice, using RAG, tool calling, and multimodal models to execute business tasks.
# 합류하게 될 팀에 대해 알려드려요 - AI Manager는 토스 Data Division의 AI Tribe에 소속되어 있어요. - AI Tribe는 토스의 중앙 AI 조직으로 전사의 ML/AI Platform을 제공하며 공통화된 ML/AI 모델을 제공하는 팀으로 구성되어 있어요. - 개별 요청을 해결하는 데 그치지 않고, 반복되는 문제와 공통 요구를 여러 제품과 조직이 활용할 수 있는…
# 합류하게 될 팀에 대해 알려드려요 - IT Strategy Manager는 기술 전략을 담당하는 Tech Excellence Tribe 산하 IT Planning Team에 소속되어요. (입사 후 내부적으로 통용되는 직무 명칭은 IT Planning Manager 로 동일해요) - IT Planning Team은 규정 준수만 담당하는 지원 조직이 아니에요. 인프라, 플랫폼, 데이터,…
The Data Analytics Engineer on Toss Bank’s Data Warehouse team builds and operates large‑scale data pipelines and marts using Hadoop, Python/PySpark, Spark, Airflow and Data Mesh/Medallion architectures to ensure data quality and provide reliable data for the company.
합류하게 될 팀에 대해 알려드려요 Server Developer (Japan)은 Global Team에 속해 업무해요. Global Team은 일본 시장에서 현지 사용자를 위한 새로운 디지털 금융 경험을 만들고 있어요. 서버 개발자는 현지 맥락에 맞게 제품과 기술을 새롭게 설계하고, 특정 기능에 머무르기보다 여러 제품과 기술 영역을 연결하며 담당한 문제의 해결 방향과 기술적 선택을…
Designs and operates large-scale AI inference pipelines at Toss, combining ML, LLM, and Vision models to automate high-volume judgment tasks; owns end-to-end cost, throughput, and reliability (async/batch design, rate limits, failover) and helps evolve the shared AI platform across domains.
Technical Program Manager on Toss Securities' ML Platform Team: translates AI regulation (AI Basic Act, innovative financial services) into actionable AI governance standards, bridges the product and platform organizations, and manages AI/ML projects end to end, including allocation of shared GPU and on-prem/cloud AI infrastructure.
ML Engineer on Toss's Commerce AI Team designs models and data structures powering the Toss Shopping catalog — product classification, brand/attribute extraction, and matching of identical products — plus the large-scale training, batch, and online inference pipelines behind them, using PyTorch, SQL/Spark, and classic ML libraries.
Joins Toss's AI Platform team to build and run the infrastructure that serves LLM and embedding models in production — operating and tuning serving frameworks like vLLM, Triton, and Dynamo, managing GPU resources, and automating deployment, monitoring, and orchestration for stable, scalable AI services.
# 합류하게 될 팀에 대해 알려드려요 - 토스뱅크 Server Developer (Product Foundation)는 Product Foundation(제품 기반) 도메인 소속으로, 토스뱅크의 기반이 되는 제품을 만들고 있어요. - 혁신적인 은행 상품이 빠르고 안정적으로 출시될 수 있게 지원하며, 고객이 은행 서비스를 안심하고 이용할 수 있도록 공통 기반 시스템을 만들어요. - 팀원들이…
Product Owner at Toss Bank (Seoul) who turns complex internal banking problems into data products: finding where colleagues struggle, prioritizing what to build, defining data meaning/structure/quality with developers, DS, and DE, and iterating based on post-launch impact. Finance experience not required; platform/SaaS product ownership experience valued.
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