Specialist - Data Sciences
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Job description
Experteer Overview In this AI Engineer role you design and deploy production-grade AI systems focused on LLM pipelines, RAG architectures, and evaluation. You work with cross-functional teams to implement scalable, MLOps-driven solutions and evaluate model performance in real-world contexts. You will leverage leading SDKs and orchestration tools to ship reliable AI features and maintain system quality. This role offers the chance to shape how AI capabilities are integrated into products and platforms. Compensation / Benefits * Deploy production AI solutions using LangChain, LangGraph, and multiple SDKs (OpenAI, Claude) * Manage orchestration and MCP/MLOps practices to ensure reliable, scalable systems * Evaluate and fine-tune LLMs, embeddings, and RAG-based retrieval pipelines * Implement and maintain vector stores and retrieval architectures (ChromaDB, FAISS) * Develop APIs and services (FastAPI, REST) for AI features * Collaborate with cross-functional teams to integrate AI components into products Tasks * MS in Computer Science or equivalent experience * expertise in LLM systems, RAG architectures, and vector embeddings * experience deploying production AI using LangChain, LangGraph, OpenAI and Claude SDKs * hands-on with MCP orchestration and MLOps practices * proficiency in Python and JavaScript/TypeScript, and web frameworks (FastAPI, React, Spring Boot) * strong knowledge of storage and tooling (ChromaDB, FAISS, Hugging Face, Pydantic) * experience with cloud and dev tooling (AWS, Docker, CI/CD, Git) * familiarity with databases (PostgreSQL, MySQL, MongoDB) Key requirements *
Requirements
AI into products Tasks * MS in Computer Science or equivalent experience * expertise in LLM systems, RAG architectures, and vector embeddings * experience deploying production AI using LangChain, LangGraph, OpenAI and Claude SDKs * hands-on with MCP orchestration and MLOps practices * proficiency in Python and JavaScript/TypeScript, and web frameworks (FastAPI, React, Spring Boot) * strong knowledge of storage and tooling (ChromaDB, FAISS, Hugging Face, Pydantic) * experience with cloud and dev tooling (AWS, Docker, CI/CD, Git) * familiarity with databases (PostgreSQL, MySQL, MongoDB) Key requirements *
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