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Build production-grade AI features like RAG pipelines and agentic workflows using Python, FastAPI, and vector stores; ship LLM-powered services end-to-end.
Design and deploy AI/ML models, including LLMs and GenAI, to solve healthcare data challenges using Python, cloud platforms, and MLOps.
Build and deploy multi-agent AI systems using LLM APIs, agent frameworks, and AWS services, focusing on execution and integration rather than design.
Build and deploy AI-powered applications using LLMs, RAG pipelines, and vector search. Integrate LLM APIs into production systems with Python and cloud tools.
Builds AI-powered websites, chatbots, and voice agents for UK clients by engineering prompts, integrating APIs, and automating workflows using modern AI platforms.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to improve search, recommendations, and automation.
Build and integrate AI-powered features for a large automotive marketplace, using LLMs, RAG, and cloud services to automate workflows and improve user experience.
Build and ship AI-powered agentic applications using Python, LangChain/LangGraph, and vector databases; lead system design, DevOps, and team mentorship.
Build production-grade AI agents and LLM-powered features like chatbots and RAG systems using Python, FastAPI, and third-party models (OpenAI, Gemini, Claude).
Build and deploy production AI systems, including LLM-powered chatbots and RAG pipelines, using Python/Node.js and cloud infrastructure.
Build and scale Airweave’s distributed data pipelines, vector databases, and LLM inference infrastructure to power thousands of AI agents reliably at scale.
Build and maintain AI-powered travel systems, including data infrastructure, scalable APIs, and LLM-based prototypes in Python, to power millions of user experiences.
Build and scale the backend platform that powers AI-driven travel experiences, integrating ML models and vector search for real-time personalization at global scale.
Build full-stack web apps and AI-powered tools using React, Python, and LangChain/LangGraph, integrating RAG workflows and LLM APIs in a regulated bank’s analytics team.
Build and deploy backend services for AI/ML models, integrating LLMs, vector databases, and RAG pipelines using Python, FastAPI, and cloud platforms.
Builds and scales data pipelines, crawlers, and semantic search systems using Golang/Node.js, MongoDB, PostgreSQL, and vector databases to power AI-driven financial analytics and RAG workflows.
Build and scale data pipelines, crawlers, and semantic search systems using Golang/Node.js, PostgreSQL, and vector databases to power AI-driven financial analytics and RAG integrations.
Mô tả công việc: Key Responsibilities Data Engineering Pipelines Build and maintain data pipelines for Amazon SP-API, Advertising API, and other e-commerce platforms. Collect and process product reviews, sales,…
Build and scale backend services for AI-powered voice assistants and call-center platforms using Python, LLMs, STT/TTS, and real-time voice pipelines.
Design and build LLM-powered multi-agent systems for digital banking using Google ADK and LangGraph, integrating RAG pipelines, tool calling, and robust orchestration for production deployment.
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