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Lead a team building real-time and batch data pipelines, semantic layers, and AI-driven insights for restaurant merchants using React, TypeScript, Java, and modern data tools like dbt and ClickHouse.
Build and own backend systems powering AI creative tools: SvelteKit apps, Postgres/Redis/ClickHouse data layers, Python ML inference services, and Kubernetes clusters across cloud providers.
Team lead for AI/ML projects: organizes DS/ML teams, sets LLM pipelines (RAG, fine-tuning), translates business needs into technical tasks, and ensures model quality and deployment in production.
Build and deploy LLM-backed AI agents for banks and hedge funds, integrating cloud and on-prem models, tool use, and retrieval systems to solve client problems.
Build and maintain automated test suites for an AI-driven data platform (FastAPI, PostgreSQL, ClickHouse) and review AI-generated tests to ensure enterprise-grade reliability.
Designs data architecture for telecom systems (RAN, Transport, Core), integrates OSS/BSS data, validates KPIs (availability, latency, MTTR), builds dashboards (Power BI/Tableau/Grafana), and automates calculations with Python/SQL/Airflow.
Build and scale FastAPI-based REST services, set up CI/CD, and deploy ML models in a high-load ecommerce environment using Python, Kubernetes, and MLOps tooling.
Build and maintain low-latency trading infrastructure for crypto liquidity, including exchange connections, automated quoting bots, and risk systems using Java/Rust/C++ and FIX/WebSocket.
Design and build real-time and batch data pipelines using Apache Flink to power analytics and ML features for a global crypto exchange.
Build and operate a high-throughput crypto market-data platform: ingest exchange APIs, run streaming/batch pipelines, and maintain storage backends (Iceberg, ClickHouse, MySQL/PostgreSQL) to feed trading desks, quants, and analytics.
Build and operate low-latency crypto trading infrastructure, including venue connectivity, automated pricing strategies, and risk systems for a global exchange.
Build and maintain the distributed data platform (Spark, MaxCompute, Hologres) that powers OKX’s crypto exchange, and integrate LLM-driven agents for scheduling, cost optimization, and incident response.
Build and maintain Python-based backend services and REST APIs for a blockchain transaction monitoring platform, using Django/FastAPI, PostgreSQL, and Redis.
Leads a team of data scientists to design, build, deploy, and monitor ML models end-to-end, bridging business needs with technical execution in a fintech environment.
Build and own production-grade infrastructure for real-time ML systems, feature serving, and decisioning at a fast-growing European fintech.
Java Data Engineer (Streaming) at Exness constructs and maintains scalable data platforms using Java, Kafka, Flink, and related technologies, focusing on data integration, ETL pipelines, and infrastructure for trading solutions.
DevOps engineer ensures zero-downtime deployments, automates infrastructure tasks (CI/CD, backups, monitoring), and optimizes database performance for a media/affiliate SaaS company using Docker, GitHub Actions, PostgreSQL, and Nginx.
Principal engineer building Salesforce’s unified observability platform: metrics, logs, and traces with AI-first tooling, Java backends, React/LWC frontends, and OpenTelemetry/Kafka stacks.
QA engineer tests web apps and backend services, focusing on Linux/Unix console workflows, API testing, and test-case design for a modern PHP/Go/Python stack.
Зарплата: от 207000 RUR (до вычета налогов) Работа в офисе в г. Краснодар. Удаленный формат занятости не предусмотрен. МедРокет — уникальная платформа IT-решений для медицины создаем удобные продукты для клиник, врачей…
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