ML / AI Engineer (LLM and NLP Systems)

Role overview

Responsibilities

• check_circle Design and productionize LLM powered pipelines for document analysis, entity extraction, issue identification, and insight generation
• check_circle Advance our multi step retrieval and reasoning workflows over large, heterogeneous document collections
• check_circle Own integrations across multiple model providers and self hosted inference infrastructure
• check_circle Optimize inference performance, latency, and cost across hosted and self managed model deployments
• check_circle Develop and refine prompts and structured outputs for complex legal and investigative use cases
• check_circle Improve hybrid search quality across semantic embeddings and traditional full text retrieval
• check_circle Build evaluation and benchmarking frameworks to continuously raise model quality and reliability
• check_circle 3+ years building production ML or NLP systems
• check_circle Deep experience working with modern LLM APIs and orchestration patterns
• check_circle Hands on experience with self hosted model serving such as vLLM, TGI, or similar
• check_circle Strong Python skills and comfort with concurrent or distributed processing
• check_circle Experience with vector search and embedding pipelines
• check_circle Solid understanding of retrieval augmented generation and model evaluation
• check_circle Bonus: background in legal tech, document intelligence, or information retrieval at scale

About the company