Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Наша цель — улучшать опыт клиента, предупреждая и предиктивно решая его проблемы и возникающие вопросы. Мы работаем с ключевыми продуктами банка и экосистемы Сбера (от дебетовых карт до СберПрайма) и стремимся сделать…
Мы разрабатываем AI-помощников для автоматизации поддержки клиентов Сбербанка в каналах чата. Наши решения на основе ML и LLM самостоятельно обрабатывают вопросы, сокращая нагрузку на операторов и обслуживая до 50+ млн…
Design and implement big data solutions, program in Scala/Python/Java/SQL, work with Hadoop ecosystem and cloud infrastructure (AWS), and tune Spark for large-scale data processing.
ИТ B2C — самая крупная экосистема в Сбере. Нас более 8000 человек в 18 городах России. Мы занимаемся разработкой и развитием розничных решений, помогая сделать сервисы Банка доступнее, безопаснее и удобнее. Ждем именно…
Build and maintain machine learning pipelines and production systems for credit scoring, fraud, and risk models at a fast-growing fintech company.
Мы ищем специалиста по работе с искусственным интеллектом и машинным обучением, готовых решать амбициозные задачи в сфере HR-технологий Сбербанка. Если ты хочешь создавать инновационные продукты и сервисы, влияющие на…
Principal Engineer building scalable data platforms, ETL/ELT pipelines, and data architectures for BCG Expand's financial services benchmarking products, using Python/SQL/Java, cloud platforms, and various database technologies.
Develop scalable Java/Spring Boot applications and design big data pipelines using Hadoop, focusing on automation, reliability, and CI/CD within a UK-based engineering team.
A software engineer role focused on building scalable Java/Spring Boot applications and big data processing solutions with Hadoop and Ansible, requiring DV clearance for a government-related project in Gloucester.
Builds and operates financial-data products for Toss Core, designing scalable DW models and BI strategies to unify revenue, cost, asset, and liability data across the org.
Designs and maintains data models for Toss’s commerce, ads, payments, growth, and business domains, ensuring reliable, standardized data for analytics and product development using SQL, Python, and Hadoop.
Designs and operates scalable data pipelines (ingestion, streaming, batch) for real-time user behavior analytics, enabling targeting, recommendations, and performance tracking in a fintech platform. Core techs: Spark, Kafka, Flink, Airflow, and distributed storage (HBase, Cassandra).
Build and refine CI/CD pipelines and Kubernetes-based infrastructure for Toss Securities, focusing on developer experience and robust monitoring to enable rapid, safe deployments.
ML Engineer at Toss builds and deploys recommendation, search, and AI models across fintech and ecommerce to optimize product exposure, CTR, and user experience using PyTorch, Spark, and Kubernetes.
Security Engineer in the Security Purple Team, responsible for designing, building, and operating SIEM (Splunk, Opensearch, Elasticsearch) and log pipelines (NIFI, KAFKA, Hadoop) across On-Prem, AWS, and K8S environments, focusing on log collection, analysis, and automation.
Builds and maintains scalable backend services powering Toss’s fintech products like payments, loans, and ads using Kotlin/Spring, MySQL, Kafka, and Redis.
Builds and scales high-traffic ad-serving backends for Toss’s in-app ad platform, using Kotlin/Spring and distributed systems like Kafka and Redis.
Builds and operates core commerce systems (search, recommendations, orders, payments, ads) for Toss Shopping, a fast-growing B2C marketplace, using Kotlin/Spring and distributed data stacks.
Builds and operates scalable backend systems for a Korean fintech super-app’s financial marketplace, handling loans, cards, insurance, and accounts while integrating AI-driven automation.
Builds and maintains the backend for Toss’s consumer-facing apps (payments, shopping, ads, etc.) using Kotlin, Spring, and distributed systems at scale.
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