Senior Machine Learning Engineer III
RELX is hiring a Senior Machine Learning Engineer III. Level rates it ; you can apply on RELX.
Level's read on this job
- Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
- Tools and skills the posting cites include LangChain, Pinecone and Qdrant.
- Level classifies it as a senior role.
- Level lists 791 other open roles at RELX.
AI in this role
Design, build, and optimize Retrieval-Augmented Generation (RAG) applications and trustworthy AI solutions for legal technology.
Are you passionate about building trustworthy Generative AI solutions that deliver accurate, source-grounded results?
Do you enjoy solving complex retrieval and search challenges while shaping the next generation of AI-powered legal and professional technology?
About our Team
LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (http://www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).
About the Role
We are seeking an AI Engineer focused on Retrieval-Augmented Generation (RAG) to help design, build, and optimize AI-powered experiences. In this role, you will contribute to the development of retrieval systems, evaluation frameworks, and source-grounded Generative AI solutions that enable users to access trustworthy and relevant information. You will work with advanced AI technologies while helping ensure quality, accuracy, and responsible AI practices.
Responsibilities
- Design, build, and optimize Retrieval-Augmented Generation (RAG) 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.
Requirements
- Hands-on experience with Retrieval-Augmented Generation (RAG) applications, including document ingestion, chunking, embedding generation, retrieval, reranking, and source-grounded responses.
- Strong understanding of Generative AI and LLM 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.
Preferred Qualifications
- Experience building AI agents or multi-step workflows with tool use, memory, and human review.
- Familiarity with agentic and LLM frameworks such as Google ADK, LangChain, LiteLLM, or MCP.
- Experience with hybrid search strategies combining keyword, metadata, semantic/vector search, and reranking.
- Experience applying RAG or Generative AI to legal, financial, publishing, or other highly regulated content domains.
- Knowledge of LLM observability, including monitoring latency, cost, retrieval performance, and unsafe or unsupported outputs.
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business
LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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How we rate this
Senior Machine Learning Engineer III at RELX rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in machine learning engineer jobs at this level
Pay
- Typical machine learning engineer job
- $199k
This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you think about the risk of an AI system in this kind of role failing silently?
- Tell me about a project where generative ai was part of your work. What did you do?
- Tell me about a project where information retrieval was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, AI Safety, Generative AI, and Information Retrieval. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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