Senior Machine Learning Engineer

Salary: $118,300 - 219,800 per year Requirements: We require a bachelors degree in Computer Science, Engineering, or a closely related discipline. We want strong experience building and scaling production ML/LLM systems. We need deep experience developing LLM applications, including RAG and prompt orchestration. We require experience designing and implementing agentic systems with agent frameworks such as LangChain, LangGraph, AutoGen, or Google ADK, including multi-step workflow orchestration in production. We need strong experience with hybrid search approaches, embeddings, and search platforms such as Solr or OpenSearch. We require expertise in distributed systems and cloud-native development, including AWS services such as S3 and DynamoDB. We need experience with streaming and messaging tools such as Kafka and SQS, plus caching technologies such as Redis. We require proficiency in Python and experience with systems languages such as Rust, Go, or Scala. We need experience building scalable APIs, including REST and GraphQL. We require experience with containerization and orchestration tools such as Docker and Kubernetes. We want strong software engineering fundamentals, including system design, testing, and CI/CD. Preferred experience includes LLM platforms such as ChatGPT/OpenAI, Claude, Gemini, LangChain, or Google ADK. Preferred experience includes DevOps and infrastructure-as-code tools such as Terraform, CloudFormation, or Jenkins. Preferred experience includes big data technologies such as Spark or Hadoop. Preferred experience includes familiarity with graph databases such as Dgraph, Neo4j, or Neptune. Preferred experience includes building high-availability, low-latency systems. Preferred experience includes work in legal or regulatory domains. Responsibilities: We architect and deliver scalable ML/LLM systems in production. We build and deploy LLM applications, including RAG pipelines and agentic systems. We implement hybrid search systems using semantic and lexical techniques, embeddings, and search platforms. We develop and support APIs, microservices, and model-serving infrastructure. We build data pipelines and streaming systems for large-scale processing. We create reusable frameworks, libraries, and shared AI/ML infrastructure across teams. We optimize systems for latency, scalability, reliability, and cost efficiency. We establish best practices for deployment, monitoring, observability, and CI/CD. We partner with Data Scientists to productionize models and integrate them into products. We provide technical leadership in system design and engineering standards. Technologies: AI AWS OpenSearch Architect Big Data ChatGPT CI/CD Cloud DevOps Docker GraphQL Hadoop Support Jenkins Kafka Kubernetes LLM Machine Learning Neo4J Python RAG REST Redis Rust Scala Solr Spark Terraform microservices Model Serving More: We are collaborating with hackajob to connect with exceptional professionals for this full-time Consultant-level Machine Learning Engineer role based in Raleigh, NC, with a hybrid schedule of three days in the office. We are focused on leading the implementation and scaling of AI systems for legal products, with an emphasis on system architecture, infrastructure, and productionizing ML/LLM solutions. The role works closely with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems. We offer a country-specific benefits package, and this position is eligible for an annual incentive bonus. The posted U.S. national base pay range is $118,300 to $219,800, with possible geographic differentials depending on location. last updated 36 week of 2026