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 agentic systems using frameworks like LangChain, including workflow orchestration.
Experience with hybrid search systems and search platforms such as Solr or OpenSearch.
Expertise in distributed systems and cloud-native development, especially with AWS.
Proficient in Python; familiar with languages like Rust, Go, or Scala.
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 using embeddings and various 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 AI/ML frameworks across teams.
Optimize systems for latency, scalability, and reliability.
Benefits
Country-specific benefits beyond standard offerings.
Improved work-life balance with hybrid scheduling.
Incentive bonus eligibility based on performance.
Full Job Description
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).
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.
About Relx Group
RELX Group is a global provider of information-based analytics and decision tools for professional and business customers. The company operates in four market segments: scientific, technical and medical; risk and business analytics; legal; and exhibitions. RELX's products and services include electronic databases, online information services, workflow tools, and print and digital books. The company was founded in 1993 and is headquartered in London, England.
