Senior AI/ML Engineer, Knowledge & Retrieval Systems

B.S. in Computer Science, Engineering, or equivalent practical experience 2–4 years of experience in applied ML, information retrieval, or knowledge systems Strong Python programming skills Experience with semantic search, vector stores, and retrieval system design Comfort with ETL workflows and structured, domain-specific datasets Understanding of distributed systems and performance trade-offs Familiarity with testing and evaluating information retrieval systems Understanding of security considerations in data handling and system design Familiarity with containerization and orchestration tools (Docker, Kubernetes)

Design and build hybrid retrieval systems that combine semantic, symbolic, and graph-based methods Develop pipelines to encode and retrieve operational knowledge using LLMs, vector databases, and custom chunking/indexing strategies Build and optimize retrieval-augmented generation (RAG) systems for high-stakes environments Architect knowledge graphs and integrate them into retrieval workflows Collaborate with ML, product, and domain experts to transform requirements into deployable solutions