Senior MLOps Engineer: Flexible Hours & AI Platforms

RELX International; Greater London; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Comprehensive Pension Plan

Generous vacation entitlement

Sabbatical leave

Parental leave

Employee discounts

Employee Assistance Program

Job summary

Elsevier, a global leader in information and analytics, seeks a Senior MLOps Engineer to bridge data science and engineering. You will build scalable ML platforms, automate pipelines, and optimize AI-driven features across cloud environments while ensuring governance and reproducibility.

The role focuses on GenAI, IR, and knowledge-graph based retrieval inside a research framework. You will collaborate with data scientists and engineers, implement CI/CD for ML, and contribute to cost

Qualifications

• Extensive experience in ML engineering and MLOps platforms for production.
• Hands-on with cloud vendor solutions and ML tooling.
• Experience with NLP/IR/GenAI and graph knowledge tooling.

Responsibilities

• Automate and orchestrate ML workflows across major cloud platforms.
• Maintain model registries and artifact stores for reproducibility.
• Develop CI/CD pipelines for ML models and data validation.
• Implement ML engineering with SageMaker, MLflow, Azure ML.
• Build SageMaker pipelines for recommender systems.
• Design GAR+RAG components and guardrails for LLMs.

Skills

Python

Java

Scala

ML Engineering

MLOps

Cloud Platforms

Search/IR

GenAI

NLP

Tools

AWS SageMaker

MLflow

Azure ML

Databricks

Elasticsearch/OpenSearch/Solr

Neo4j

PyTorch

TensorFlow

Spark

Job description

Elsevier, a global leader in information and analytics, seeks a Senior MLOps Engineer to bridge data science and engineering. You will build scalable ML platforms, automate pipelines, and optimize AI-driven features across cloud environments while ensuring governance and reproducibility.

The role focuses on GenAI, IR, and knowledge-graph based retrieval inside a research framework. You will collaborate with data scientists and engineers, implement CI/CD for ML, and contribute to cost