Senior Machine Learning Engineer III

Archer; Raleigh (NC); Hybride; USD 118 000 - 220 000; Plein temps

Résumé du poste

Archer in Raleigh, NC, is seeking a Consultant-level Machine Learning Engineer to lead production ML/LLM systems for legal products. This full-time role is hybrid—3 days in office—and focuses on scalable architecture and deployment.

You will collaborate with Data Scientists to transform validated models into reliable customer-facing systems, build RAG pipelines, and drive best practices in CI/CD and observability.

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).

Responsabilités

• 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.

Connaissances

ML systems

RAG pipelines

LangChain

Python

Distributed systems

AWS

Kubernetes

Docker

REST/GraphQL

CI/CD

LangGraph

AutoGen

Google ADK

Formation

Bachelor’s degree in CS/Engineering

Outils

Solr

OpenSearch

Kafka

SQS

Redis

DynamoDB

Terraform

CloudFormation

Jenkins

Docker

Description du poste

Archer is collaborating with LexisNexis to connect them with exceptional professionals for this role.

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.

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