MLOps Engineer – GenAI, RAG & Scalable ML Pipelines

Magno IT Recruitment; Amsterdam; Hybrid; EUR 51,000 - 85,000; Full time

Job summary

Magno IT Recruitment seeks an experienced MLOps/ML engineer for a permanent role in Amsterdam or London. The position focuses on transforming NLP/IR and GenAI models into scalable production services.

You will work at the intersection of data science and engineering, handling large data collections and AI-driven capabilities. The role emphasizes building robust ML pipelines, governance, and cutting-edge AI techniques with a strong Cloud and CI/CD focus.

Qualifications

• Minimum 4 years of experience in ML engineering or MLOps delivering ML, search, or GenAI systems to production.
• Strong Python programming skills; experience with Java or Scala is a plus.
• Experience developing and maintaining CI/CD pipelines.
• Solid understanding of ML theory, statistical analysis, and NLP.
• Hands-on experience with major cloud platforms (AWS/Azure/Google) and related AI services.

Responsibilities

• Automate and orchestrate machine learning workflows across major cloud and AI platforms.
• Maintain and manage model registries and artifact repositories for reproducibility, versioning, and governance.
• Develop and maintain CI/CD pipelines for ML systems, including data validation and deployment.
• Implement ML engineering solutions using ML Ops platforms and tooling.
• Build and maintain end-to-end pipelines for ML-driven recommendation systems.
• Design components for retrieval-augmented generation systems, including query interpretation and embeddings.

Skills

Python

CI/CD

Cloud platforms

NLP

ML engineering/MLOps

ML theory

PyTorch/TensorFlow

Spark

Search/Vector DBs/Graph DBs

Tools

Elasticsearch/OpenSearch/Solr

Neo4j

Apache Spark

PyTorch

TensorFlow

Job description

Magno IT Recruitment seeks an experienced MLOps/ML engineer for a permanent role in Amsterdam or London. The position focuses on transforming NLP/IR and GenAI models into scalable production services.

You will work at the intersection of data science and engineering, handling large data collections and AI-driven capabilities. The role emphasizes building robust ML pipelines, governance, and cutting-edge AI techniques with a strong Cloud and CI/CD focus.