Senior Machine Learning Engineer III

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 building and scaling—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.

Location:

Raleigh, NC (Hybrid – 3 days in office). Full-time position.

• 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 product ionize models and integrate into products.
• Provide technical leadership in system design and engineering standards.

• 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., Lang Chain, Lang Graph, Auto Gen, 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, Open Search).
• Expertise in distributed systems and cloud‑native development, including AWS (S3, Dynamo
  
  DB).
• 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/Graph
  
  QL).
• Experience with containerization and orchestration (Docker, Kubernetes).
• Strong software engineering fundamentals (system design, testing, CI/CD).

• Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, Lang Chain, Google ADK).
• Experience with Dev Ops and infrastructure as code (e.g., Terraform, Cloud Formation, 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.

• 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.

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 provide country‑specific benefits.  to access benefits specific to your location.

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.