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Senior Machine Learning Engineer III

Role overview

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 hybrid search (semantic + lexical), embeddings, and search platforms

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
  • Collaborate with Data Scientists to productionize models and integrate into products

Key facts

Hard skills

Other skills

  • Collaboration
  • Problem Solving
  • Communication

About the company

Cirium logo

Cirium

Data Analytics & Business Intelligence

Cirium® is transforming the worlds of aviation and travel with smart data and advanced analytics solutions. Cirium brings together powerful aviation analytics and data to keep the world moving. Delivering insight built from decades of experience in the sector, enabling travel companies, aircraft manufacturers, airports, airlines and financial institutions, among others, to make logical and informed decisions which shape the future of travel, growing revenues and enhancing customer experiences. Cirium is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. Track airline and airport reliability with Cirium's monthly and annual On-Time Performance reports. https://www.cirium.com/on-time-performance/ See how to Elevate your business with Cirium, the world’s most trusted Aviation Analytics company: https://www.youtube.com/watch?v=_tR8VXlzWvo

Company details

Company typeSME
IndustryData Analytics & Business Intelligence
Company size501 - 1000

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Job description

Are you looking to develop your Machine Learning Engineer career?

Do you enjoy coaching others to achieve high standards?


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.







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