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Lead a team building scalable data pipelines and infrastructure for an AI-driven platform, designing systems for vector search, ML workflows, and real-time analytics using Python, Spark, Kafka, and vector databases.
Builds AI-assisted data pipelines to parse undocumented industrial codebases into structured documentation using Python, Neo4j, Qdrant, and LLMs.
Lead AI engagements, design full-stack systems, and deploy production-ready prototypes using React, Python, and RAG architectures for enterprise clients in Kyndryl’s Frisco lab.
Builds full-stack web apps in Python (Flask/Django) with React/TypeScript front ends, integrating LLM capabilities via RAG and processing large datasets with PostgreSQL, ArangoDB, and vector search.
Qdrant is an open-source vector search engine powering the next generation of AI applications, from semantic search and retrieval-augmented generation (RAG) to AI agents and real-time recommendations. Trusted by global…
Build enterprise-grade web apps using Angular for the front end and .NET Core for back-end APIs and SQL databases, optimizing performance and collaborating with cross-functional teams.
Build and deploy enterprise LLM applications, RAG systems, and AI agents using open-source models (DeepSeek, Qwen, Kimi) and frameworks like LangChain and vLLM.
Build and maintain production-grade GenAI agents in Python, integrating LLM tool-calling, RAG pipelines, and real-time speech/data systems for enterprise clients.
Design and deploy production-ready AI systems, including LLM apps, RAG pipelines, and voice AI, for clients across healthcare, ecommerce, travel, and other sectors.
Build and deploy enterprise-grade AI systems, including LLM agents, retrieval pipelines, and AI gateways, using Python/TypeScript and modern AI engineering patterns.
Design and deploy autonomous AI agents using LLM/RAG to automate media planning, ad buying, and financial audits for an ad-tech client, covering the full lifecycle from modeling to production.
Fullstack-разработчик проектирует и пишет корпоративные веб-приложения на Python/FastAPI, Node.js и React, внедряет AI/RAG-решения и интегрирует корпоративные сервисы.
ML/AI инженер разрабатывает и масштабирует модели для автоматизации бизнес-процессов в государственной цифровой платформе, используя Python, PyTorch, NLP/LLM и MLOps-инструменты.
Builds and deploys LLM/NLP-based AI agents, RAG systems, and GenAI pipelines using Python, FastAPI, and PyTorch for enterprise clients.
Builds and maintains robust LLM-based AI agents and RAG pipelines, designs multi-step reasoning workflows, and implements quality evaluation frameworks to ensure reliable, production-grade AI systems.
Senior ML Engineer designs, builds, and deploys cloud-based AI/ML solutions, leads MLOps practices, and mentors junior team members using Python, FastAPI, and cloud services like AWS/GCP.
Build and scale backend services for Constructor’s AI-powered e-commerce search platform, focusing on ML infrastructure, model serving, and distributed systems.
Tech Lead DevOps/MLOps Engineer builds and runs the AI platform’s infrastructure, deploys LLM models, and maintains Python/Java apps, Kubernetes clusters, CI/CD, and databases in production.
Build and scale an internal AI platform using LLMs, vector databases, and agent frameworks to automate engineering workflows and create AI assistants for sales, design, manufacturing, and leadership.
Ищем Java/Kotlin разработчика для разработки сервисов AI-платформы. Специалист будет отвечать за разработку Java-приложений и стабильную работу AI-сервисов.### Твои задачи: * разработка функциональности системы в…
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