Senior Machine Learning Engineer III

Consultant-Level Machine Learning Engineer

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.

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.