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Data Scientist develops and deploys AI/ML solutions for a bank’s internal digital products, focusing on improving AI system quality, user context handling, and product applications. Daily work involves solving complex ML tasks, designing evaluation pipelines, and integrating models into product infrastructure.
A bank is hiring a Senior Product Engineer to develop its in-house collateral management platform, owning features end-to-end from business analysis through implementation to production support. Core stack: C#/.NET backend, PostgreSQL, Kafka/RabbitMQ, REST APIs, and React, with CI/CD and observability in a LeSS multi-team setup.
Product engineer on a bank's foreign-economic-activity (ВЭД) product team: designs architecture and builds/maintains Java microservices (Spring, Camel), integration solutions (MQ, REST), and Kubernetes-based deployments, while improving CI/CD, writing autotests, and applying basic AI/ML concepts. Remote or office work in Russia.
Leads a data-analytics team building ML/AI-driven personalization, A/B-testing, and metrics systems for a retail-banking product used by millions.
Research LLM Engineer builds, fine-tunes, and deploys specialized large language models for banking tasks, optimizing price/performance from training to production inference.
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