Our client is seeking a Data Scientist for a direct hire opportunity.

Responsibilities

Design and deploy production-ready AI systems that leverage LLMs and advanced ML
Build and maintain multi-agent systems and agentic orchestration workflows using frameworks like LangChain, LangGraph, or AutoGen
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines, ensuring high-fidelity context retrieval
Implement and extend MCP (Model Context Protocol) servers to allow LLMs to interact safely and efficiently with local and remote data sources
Architect robust, scalable APIs and microservices to serve AI features to end-users with low latency
Collaborate with product partners and other scientists to identify new opportunities to apply AI / ML to products
Conduct research and identify AI / ML algorithms and methods to solve specific business problems, and deliver these algorithms as microservices
Implement rigorous testing and evaluation frameworks for LLM outputs to ensure prompt stability, prevent regressions, and manage hallucination
Contribute towards the common data science platform

Requirements

5+ years of experience developing AI / ML applications
Substantial depth and breadth in NLP, Deep Learning, Generative AI, LLMs, and other state of the art AI
Experience with LLM orchestration frameworks such as LangChain
Expert-level knowledge of LLM APIs (OpenAI, Anthropic Claude) and open-source models (Llama, Mistral)
Deep understanding of CS fundamentals and computational complexity
Experience with building large-scale distributed systems in an agile environment and the ability to build quick prototypes
Excellent knowledge of Python and core data science and AI libraries including Pandas, NumPy, PyTorch
Experience building or utilizing Model Context Protocol (MCP) server
Strong background in scalable backend environments (Docker, Kubernetes, AWS/GCP)
Experience moving AI from prototype to production-grade services with monitoring, logging, and rate-limiting
Ability to independently conduct research and develop appropriate algorithmic solutions to complex business problems

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