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LexisNexis Legal & Professional

Legal, government, and business intelligence platform

Senior Machine Learning Engineer 3

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeMexico City, CDMX, MexicoNo salary listedIn-person

About the Job

Requirements

  • Hands-on experience with Retrieval-Augmented Generation applications, including document ingestion, chunking, embedding generation, retrieval, reranking, and source-grounded responses.
  • Strong understanding of Generative AI and large language model capabilities, limitations, hallucination mitigation, and response-quality evaluation.
  • Experience designing and operating vector search solutions using Qdrant, Pinecone, pgvector, LanceDB, OpenSearch vector search, or equivalent technologies.
  • Ability to validate retrieval quality, citation accuracy, relevance, coverage, and factual grounding using reproducible evaluation datasets.

Responsibilities

  • Design, build, and optimize Retrieval-Augmented Generation applications.
  • Develop and manage document ingestion, chunking, embedding generation, retrieval, reranking, and source-grounded response workflows.
  • Design and operate vector search solutions using modern vector database technologies.
  • Validate retrieval quality, citation accuracy, relevance, coverage, and factual grounding using reproducible evaluation datasets.
  • Collaborate with cross-functional teams to improve response quality and reduce hallucinations.
  • Implement hybrid search strategies combining keyword, metadata, semantic/vector search, and reranking techniques.
  • Monitor and evaluate retrieval performance, latency, cost, and AI system quality.
  • Support the development of scalable and responsible Generative AI solutions across legal and professional information products.

Desired Qualifications

  • Experience building AI agents or multi-step workflows with tool use, memory, and human review.
  • Familiarity with agentic and large language model frameworks such as Google ADK, LangChain, LiteLLM, or MCP.
  • Experience with hybrid search strategies combining keyword, metadata, semantic/vector search, and reranking.
  • Experience applying Retrieval-Augmented Generation or Generative AI to legal, financial, publishing, or other highly regulated content domains.
  • Knowledge of large language model observability, including monitoring latency, cost, retrieval performance, and unsafe or unsupported outputs.

About the Company

LexisNexis Legal & Professional

Legal, government, and business intelligence platform

LexisNexis Legal & Professional provides legal, government, business, and high-tech information through subscription-based access to a vast repository of licensed news publications and corporate data. Its offerings, such as Nexis AI, enable advanced research, intelligence gathering, and automatic document summarization for professionals in law firms, corporations, government agencies, and academic institutions. The platform works by delivering curated information and insights from millions of companies and publications via a search and analysis interface, helping users find accurate information quickly. The company differentiates itself with a long history of service, a broad, licensed data library across multiple sectors, and AI-powered tools that streamline research and decision-making. Its goal is to help clients make informed decisions, achieve a competitive advantage, and boost efficiency by providing trusted information and tailored analytics.

Company size
5,001-10,000
Company stage
Growth Equity (Non-Venture Capital)
Total funding
$30M
Headquarters
New York City, New York
Founded
1973

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