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Департамент информационных технологий Москвы создает и развивает цифровые проекты, которые делают столицу комфортнее, а жизнь горожан — удобнее и мобильнее. Для системы управления столицей технологии — это незаменимый…
Build and deploy LLM-powered AI systems, RAG pipelines, and agent workflows using Python and cloud platforms for enterprise clients.
Designs cloud-native data platforms and AI systems using LLMs, RAG, and agentic frameworks to build scalable, intelligent solutions for enterprises and public agencies.
Build and operate secure Kubernetes-based platforms for AI-assisted software development, including GitOps, private registries, and observability, ensuring security and auditability in sovereignty-sensitive environments.
Design and automate cloud infrastructure and CI/CD pipelines for AI platforms on GCP, build MLOps pipelines with Vertex AI and RAG, and implement monitoring for LLM systems.
Builds and optimizes ETL pipelines, vector databases, and LLMOps for AI services using Python/Java/Scala, focusing on RAG/LLM workflows and multimodal data.
Build and operate an agentic AI platform for legal workflows, including orchestration, retrieval, and evaluation systems, using Python and LLM frameworks in a collaborative, startup-like team.
Build and scale the data infrastructure powering Epiq AI Labs’ legal-focused AI platform, including high-volume document ingestion, distributed processing, and vector/search indexing for retrieval and reasoning engines.
Lead enterprise Generative AI strategy, designing advanced RAG architectures and evaluation frameworks to deploy production-grade LLM systems with a focus on accuracy, safety, and business impact.
Design and build AI-powered systems that automate software delivery workflows, integrating agentic AI into R&D, product management, and DevOps toolchains.
Build and operate a secure Kubernetes-based platform for AI engineering tools, implementing GitOps and observability while ensuring sovereignty, reliability, and auditability in a high-security environment.
Boardy is an AI super-connector that helps ambitious professionals build a network that matters. We believe that talent and drive shouldn't be limited by who you know. In a world of LinkedIn spam and transactional…
Build and operate high-throughput ETL/ELT pipelines that ingest blockchain, exchange, and text data, then serve clean datasets and APIs for crypto-market analytics and risk models.
Builds and optimizes AI-powered legal RAG pipelines using Qdrant, hybrid search, and LLM providers (Anthropic, OpenAI, YandexGPT) to retrieve and rank relevant legal documents from a 23M+ corpus.
Build production-grade AI systems for investment analysis and procurement using LLM, multi-agent architectures, and RAG pipelines in Python.
Leads a DevOps team maintaining real-time video analytics infrastructure, CI/CD pipelines, and distributed storage clusters for an AI-powered surveillance platform.
Design autonomous network solutions for telecoms using AI frameworks (Vertex AI, LangGraph), APIs, and vector databases to optimize agentic systems and reduce inference costs.
Build and maintain a universal data platform that integrates enterprise data sources into automated pipelines, ensuring high-quality data for AI agents, LLMs, and RAG workflows using Python, SQL, and vector databases.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, vector/graph databases, and Kubernetes.
Build and deploy LLM-powered agents and RAG pipelines using PyTorch and Hugging Face, optimizing for accuracy, latency, and cost in a contact-center AI platform.
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