Senior Machine Learning Engineer III *Raleigh, NC*

Remitly; Raleigh (NC); Hybrid; USD 118,000 - 220,000; Full time

Job summary

Remitly in Raleigh, NC is seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. You will own system architecture, infrastructure, and productionization of ML/LLM solutions.

You will partner with Data Scientists to turn validated models into reliable, high-performance, customer-facing systems, guiding cross-functional teams in deployment, monitoring, and optimization.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience implementing and scaling production ML/LLM systems.
• LLM application development, including RAG and prompt orchestration.
• Agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK) with multi-step production workflows.
• Hybrid search (semantic + lexical), embeddings, and search platforms (Solr, OpenSearch).
• Distributed systems and cloud-native development, including AWS (S3, DynamoDB).
• Streaming/messaging systems (Kafka, SQS) and caching (Redis).
• Python proficiency and systems languages (Rust, Go, Scala).
• Experience building scalable APIs (REST/GraphQL).
• Containerization/orchestration (Docker, Kubernetes).
• Strong software engineering fundamentals (system design, CI/CD).

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 reusable frameworks, libraries, and infrastructure for AI/ML across teams.
• Optimize systems for latency, scalability, reliability, and cost.
• 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.

Skills

ML/LLM systems

Prompt orchestration

Agentic systems

Hybrid search

Python

REST GraphQL

System design

CI/CD

Distributed systems

Writ large - architecture

Education

Bachelor's degree in CS/Engineering

Tools

LangChain

LangGraph

AutoGen

Google ADK

Solr

OpenSearch

AWS

Kafka

Redis

Docker

Kubernetes

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 with 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.

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