Elsevier
Senior MLOPs
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Senior MLops
Location: Amsterdam
About our Team
Data Science Life Sciences is a diverse team focusing on GenAI, ML, NLP. We mainly develop best-in-class enrichment pipelines for Elsevier’s life science .com products such as Reaxys, Embase, and Pharmapendium.
About the Role
Join the team that powers Elsevier’s Data Scientists at Corporate Markets in the domain of Life Sciences. You will bridge Data Science and Engineering to turn experimental NLP/IR/GenAI models into secure, reliable, and scalable services. Our work empowers R&D within Chemistry and Biology domain, to support that 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 confidentiality.
Key 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-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 (NDCG, MAP, MRR), LLM quality metrics (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
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Collaboration
- Partner with Data Scientists, Engineers, Subject Matter Experts, Product Managers, and Responsible AI experts to support translating business problems into cutting-edge data science solutions
- Collaborate and interface with Operations Engineers who deploy and run production infrastructure
Required Qualifications
- 5+ years in 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 organization. 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.
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 world.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Primary Location Base Pay Range: NLD Amsterdam (Radarweg) €53,800 - €89,900. This role is covered by the Collective Labor Agreement Publishing Industry.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country-specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. 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.
Criminals may pose as recruiters asking for money or personal information. We never request money or banking details from job applicants. Learn more about spotting and avoiding scams here.
Please read our Candidate Privacy Policy.
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.
USA Job Seekers:
EEO Know Your Rights.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills