Are you looking to develop your Machine Learning Engineer career?
Do you enjoy coaching others to achieve high standards?
This is a full-time position based in Raleigh, NC.
(Hybrid - 3 days in office)
About the Role
We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role focuses on how to build and scale—owning system architecture, infrastructure, and productionization of ML/LLM solutions.
You will partner with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems.
Key Responsibilities
- Architect and implement scalable ML/LLM systems in production.
- Build and deploy LLM applications, including RAG pipelines and agentic systems.
- Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
- Develop and maintain APIs, microservices, and model serving infrastructure.
- Build data pipelines and streaming systems for large-scale data processing.
- Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
- Optimize systems for latency, scalability, reliability, and cost efficiency.
- Establish best practices for deployment, monitoring, observability, and CI/CD.
- Collaborate with Data Scientists to productionize models and integrate into products.
- Provide technical leadership in system design and engineering standards.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- Strong experience implementing and scaling production ML/LLM systems.
- Deep experience with LLM application development, including RAG and prompt orchestration.
- Strong experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK), including orchestration of multi-step workflows in production environments.
- Strong experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
- Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
- Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
- Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
- Experience building scalable APIs (REST/GraphQL).
- Experience with containerization and orchestration (Docker, Kubernetes).
- Strong software engineering fundamentals (system design, testing, CI/CD).
Preferred Qualifications
- Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, LangChain, Google ADK).
- Experience with DevOps and infrastructure as code (e.g., Terraform, CloudFormation, Jenkins).
- Experience with big data technologies (e.g., Spark, Hadoop).
- Familiarity with graph databases (e.g., Dgraph, Neo4j, Neptune).
- Experience building high-availability, low-latency systems.
- Experience in legal or regulatory domains.
Key Competencies
- Strong system architecture and scalability mindset.
- Ownership of implementation, performance, and reliability.
- Ability to translate data science solutions into production systems.
- Cross-functional collaboration with DS, product, and platform teams.
- Excellent debugging, optimization, and operational skills.
- Clear communication of technical designs and trade-offs.
#AIFluent
U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus.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.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.
Please read our Candidate Privacy Policy.
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.
USA Job Seekers:
EEO Know Your Rights.
Skills Required
- Bachelor's degree in Computer Science, Engineering, or a related field.
- Experience implementing and scaling production ML/LLM systems.
- Deep experience with LLM application development, including RAG and prompt orchestration.
- Experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK).
- Experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
- Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
- Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
- Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
- Experience building scalable APIs (REST/GraphQL).
- Experience with containerization and orchestration (Docker, Kubernetes).
- Strong software engineering fundamentals (system design, testing, CI/CD).
RELX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.
-
Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
-
Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
-
Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.
RELX Insights
What We Do
RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.
