Senior MLOps Engineer

RX Brasil; City Of London; On-site; GBP 90,000 - 125,000; Full time

Benefits offered by this job

Wellbeing programs

Shared parental leave

Study assistance

Sabbaticals

Job summary

Elsevier seeks an experienced ML Engineer to bridge Data Science and Engineering, turning experimental NLP/IR/GenAI models into secure, reliable services over one of the world’s largest scholarly corpora.

You’ll work on AI-based search, ranking, and knowledge-graph retrieval, partnering with product, data science, and Responsible AI teams to deliver scalable, governed systems using cloud platforms and industry-standard MLOps tools.

Qualifications

• Extensive experience shipping ML or search/GenAI systems to production.
• Strong programming in Python, Java, or Scala.
• Experience with NLP, ML theory, and statistical analysis.
• Hands-on with AWS, Azure, or Google cloud platforms.
• Familiarity with Elasticsearch/OpenSearch/Solr, Neo4j, or other graph/vector stores.
• Experience evaluating LLM models and governance of ML systems.
• Knowledge of scholarly publishing workflows or citation graphs is a plus.
• Understanding of the Data Science Life Cycle: feature engineering, model training, evaluation.

Responsibilities

• ML & LLM engineering for search, ranking, and recommendation.
• Automate ML workflows across major cloud platforms and foundation model APIs.
• Maintain model registries and artifact stores for reproducibility.
• Develop CI/CD for ML with data validation and deployment.
• Build SageMaker pipelines for recommendations and GAR/RAG systems.
• Design components for query interpretation, embeddings, and hybrid retrieval.
• Work with product, data science, and Responsible AI teams to translate problems into ML solutions.
• Collaborate with operations engineers to deploy production infrastructure.

Skills

ML Engineering

MLOps

Python

Java/Scala

NLP

Cloud (AWS/Azure/Google)

Elasticsearch/OpenSearch/Solr

Neo4j/Graph DBs

LLM evaluation

Data Science lifecycle

PyTorch/TensorFlow

Spark

Tools

SageMaker

MLflow

Azure ML

Job description

About the Team

Join the team that powers Elsevier’s research platforms—Scopus/Scopus AI, ScienceDirect/ScienceDirect AI, and journal submission & peer review workflows.

About the Role

You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our systems operate over one of the world’s largest scholarly corpora, so you’ll work on AI-based features (GenAI, Agentic AI, RAG, etc.) search/ranking quality, and knowledge graph aware retrieval while enforcing content rights and editorial confidentiality.

Responsibilities

• ML & LLM Engineering, Search and Recommendation Engines
• Automate and orchestrate machine learning workflows across major cloud and AI platforms (AWS, Azure, Databricks, and foundation model APIs such as OpenAI)
• Maintain and version model registries and artifact stores to ensure reproducibility and governance
• Develop and manage CI/CD for ML, including automated data validation, model testing, and deployment
• Implement ML Engineering solutions using popular MLOps platforms such as AWS SageMaker, MLflow, Azure ML
• End‑to‑end custom SageMaker pipelines for recommendation systems
• Design and implement the engineering components of GAR+RAG systems (e.g., query interpretation and reflection, chunking, embeddings, hybrid retrieval, semantic search), manage prompt libraries, guardrails and structured output for LLMs hosted on Bedrock/SageMaker or self‑hosted
• Design and implement ML pipelines that utilize Elasticsearch/OpenSearch/Solr, vector DBs, and graph DBs
• Build evaluation pipelines: offline IR metrics (e.g., NDCG, MAP, MRR), LLM quality metrics (e.g., faithfulness, grounding), and A/B testing
• Optimize infrastructure costs through monitoring, scaling strategies, and efficient resource utilization
• Stay current with the latest GAI research, NLP and RAG and apply the state‑of‑the‑art in our experiments and systems
• Collaboration: Partner with Subject‑Matter Experts, Product Managers, Data Scientists and Responsible AI experts to translate business problems into cutting edge data science solutions
• Collaborate and interface with Operations Engineers who deploy and run production infrastructure

Requirements

• Extensive experience ML Engineering, MLOps platforms, shipping ML or search/GenAI systems to production
• Strong Python, Java, and/or Scala engineering
• Experience with statistical analysis, machine learning theory and natural language processing
• Hands‑on‑experience with major cloud vendor solutions (AWS, Azure and/or Google)
• Search/vector/graph technologies (e.g., Elasticsearch / OpenSearch / Solr/ Neo4j)
• Experience in evaluating LLM models
• Background with scholarly publishing workflows, bibliometrics, or citation graphs
• A strong understanding of the Data Science Life Cycle including feature engineering, model training, and evaluation metrics
• Familiarity with ML frameworks, e.g., PyTorch, TensorFlow, PySpark
• Experience with large scale data processing systems, e.g., Spark

Work in a Way That Works for You

We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long‑term goals.

Working Pattern

Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive

About the Business

A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better worl We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Elsevier is part of RELX Group. Let’s shape progress together. Join us. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120. elsevier.com/about/careers

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Equal Employment Opportunity

We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.