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Build and improve a community-feed recommendation system for a stock-trading app used by 4 million monthly active users, using Python, PyTorch, and cloud-native serving stacks.
Designs and operates ultra-high-performance AI infrastructure (GPU clusters, InfiniBand, Kubernetes) for Toss Securities' ML services, optimizing resource use and eliminating bottlenecks.
Build and operate ML/LLM platforms for a Korean neobank, focusing on stable, scalable, and secure model training, deployment, and serving using tools like MLflow, Kubeflow, Triton, and vLLM.
Builds and operates a machine-learning platform for a securities app, focusing on LLM serving, gateway systems, and MLOps tooling in Kubernetes.
Build and maintain the core server platform for Toss’s fintech services using Java/Kotlin and Spring, focusing on scalability, monitoring, and distributed systems.
Builds and operates high-availability platform services for Toss Bank, including messaging, API gateways, monitoring, and caching, using Kotlin/Java and Spring ecosystems.
Designs and develops high-availability, scalable server systems for Toss’s offline payment solutions, focusing on system architecture, real-time traffic handling, and end-to-end service reliability using Java/Kotlin, Spring, Kafka, and cloud-native tools.
Builds and maintains scalable, secure banking services using Kotlin/Java and Spring, focusing on high-traffic systems and innovative fintech products in a collaborative squad model.
Designs, builds, and operates GPU infrastructure for AI/ML workloads, including bare-metal clusters, networking, and monitoring.
Maintains and scales Toss’s payment and financial services infrastructure to ensure high availability and performance using cloud-native tools and DevOps practices.
Builds and maintains a global financial data platform for securities, processing real-time market data with AI/ML pipelines using Kafka, Spark, and Iceberg.
Build and maintain monitoring, observability, and performance-testing systems to keep Toss Bank’s high-traffic services stable and scalable using Kotlin/Java, Kubernetes, Istio, Kafka, and Prometheus.
Senior DevOps Engineer supporting two teams maintaining a loyalty platform across seven European markets, working with Azure, AWS, CI/CD pipelines (Azure DevOps, GitHub Actions), Terraform for IaC, and Grafana/Prometheus for monitoring.
Hands-on Cloud DevOps Engineer building and operating AWS infrastructure (EKS, Terraform), improving CI/CD pipelines (Jenkins/GitLab CI), and automating operations using Python/Go/Bash.
Senior Platform DevOps Engineer owning the enterprise observability platform (Grafana Cloud, Prometheus, Thanos) and Kubernetes/OpenShift integrations for an insurance group's platform engineering team.
DevOps Team Lead for a financial-sector client, managing Linux (RHEL) environments, building CI/CD pipelines, and supporting dev teams with containerization (Docker, Kubernetes), cloud (AWS), and monitoring (Prometheus, Grafana) technologies.
DevOps Engineer at LUX MED (healthcare) in Warsaw, optimizing Kubernetes clusters, building CI/CD pipelines with GitHub Actions and ArgoCD, implementing observability (Grafana, Prometheus, OpenTelemetry, ELK), managing IaC via Terraform, and enforcing security practices.
Develop and maintain a high-volume Java-based system using Spring Boot, PostgreSQL, Elasticsearch, Kafka, and Kubernetes, with a focus on security, deployment, and monitoring.
This role involves designing and maintaining enterprise-grade observability platforms using tools like Prometheus, Grafana, and OpenTelemetry to ensure system reliability. The engineer will work across cloud-native environments, focusing on metrics, logs, traces, and automation to improve incident detection and troubleshooting.
Performance Test Architect defining and driving performance engineering strategy for Amtech's cloud-native, distributed enterprise applications — focusing on workload modeling, bottleneck analysis, capacity planning, and CI/CD-integrated performance testing using tools like JMeter, k6, and observability platforms.
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