Senior MLOps Engineer: GenAI, NLP & Scalable ML

RX Brasil; Amsterdam; Remote; EUR 54,000 - 90,000; Full time

Benefits offered by this job

Wellbeing programs

Shared parental leave

Job summary

Elsevier is seeking a Senior MLOps Engineer to bridge Data Science and Engineering, turning NLP/IR/GenAI models into secure, scalable services. You will work on AI-based features across research platforms, collaborating with data scientists and product teams to deliver reliable, production-ready pipelines.

You will design and maintain end-to-end MLOps workflows, implement guardian and retrieval systems, and optimize cost, while staying current with the latest AI research.

Qualifications

• 3–5+ years in ML Engineering or MLOps
• Strong Python/Java/Scala skills
• Experience with cloud providers (AWS/Azure/Google)
• Familiarity with NLP, ML, and GenAI
• Knowledge of vector/search/graph technologies
• Experience evaluating LLMs
• Background in scholarly publishing workflows
• Spark/large-scale data processing experience

Responsibilities

• Automate ML workflows across major cloud platforms.
• Maintain model registries and artifact stores for reproducibility and governance.
• Develop CI/CD for ML, including data validation and deployment.
• Implement ML engineering solutions using SageMaker, MLflow, Azure ML.
• End-to-end SageMaker pipelines for recommendation systems.
• Design GAR+RAG components, prompts, and guardrails.
• Build pipelines using Elasticsearch/OpenSearch/Solr, vector/graph DBs.
• Create evaluation pipelines and A/B testing for ML systems.
• Optimize infrastructure costs and resource utilization.
• Stay current with NLP, GenAI and RAG research and apply in experiments.
• Collaborate with SMEs, PMs, Data Scientists and Operations Engineers.

Skills

Python

Java/Scala

NLP

ML Engineering

Cloud Platforms

Elasticsearch

Solr

PyTorch

TensorFlow

Spark

Education

MS/PhD in CS/ML

Tools

MLflow

SageMaker

Azure ML

Git

Job description

Elsevier is seeking a Senior MLOps Engineer to bridge Data Science and Engineering, turning NLP/IR/GenAI models into secure, scalable services. You will work on AI-based features across research platforms, collaborating with data scientists and product teams to deliver reliable, production-ready pipelines.

You will design and maintain end-to-end MLOps workflows, implement guardian and retrieval systems, and optimize cost, while staying current with the latest AI research.