MLOps Engineer

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

Job Description

Are you a MLOps and eager to consider a new challenge? How about a permanent job opportunity at a Data Analytics Company in Amsterdam or London?

General Information

Duration: Intention of a permanent contract after 12 months

No. of working hours: 36 hours per week

Location: 1 to 2 times a week in the Amsterdam office

Contract type: Employment / Direct Hire

Salary: max 85.000 in Euro or GBP incl holiday allowance and 13th month

What is the project about?

In this role, you will work at the intersection of Data Science and Engineering, helping transform experimental natural language processing (NLP), information retrieval (IR), and generative AI models into secure, reliable, and scalable production services.

The platforms process extremely large collections of structured and unstructured research data. You will contribute to the development of AI-driven capabilities such as generative AI applications, retrieval-augmented generation (RAG), intelligent search and ranking, recommendation systems, and knowledge graph–based retrieval, while ensuring compliance with data governance and content confidentiality requirements.

Key Responsibilities

• Automate and orchestrate machine learning workflows across major cloud and AI platforms.


• Maintain and manage model registries and artifact repositories to support reproducibility, versioning, and governance.


• Develop and maintain CI/CD pipelines for machine learning systems, including automated data validation, model testing, and deployment.


• Implement machine learning engineering solutions using widely adopted MLOps platforms and tooling.


• Build and maintain end-to-end pipelines for machine learning–driven recommendation systems.


• Design and develop engineering components for retrieval-augmented generation systems, including query interpretation, document chunking, embeddings, hybrid retrieval, and semantic search.


• Manage prompt libraries, guardrails, and structured outputs for large language model integrations.


• Design and implement machine learning pipelines that integrate search engines, vector databases, and graph databases.


• Develop evaluation pipelines using both traditional information retrieval metrics (e.g., NDCG, MAP, MRR) and LLM evaluation metrics such as factual grounding and response quality.


• Conduct controlled experiments and A/B testing to measure system improvements.


• Optimize infrastructure performance and cost through monitoring, scaling strategies, and efficient resource utilization.


• Stay current with advances in generative AI, natural language processing, and retrieval techniques, and apply relevant innovations to ongoing experimentation and system development.

Collaboration

Work closely with domain specialists, product stakeholders, data scientists, and responsible AI experts to translate business challenges into data-driven and AI-based solutions.

Collaborate with engineering and operations teams responsible for deploying and maintaining production infrastructure.

Requirements

• Minimum 4 years of experience in machine learning engineering or MLOps, delivering ML, search, or GenAI systems to production environments.


• 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 (AWS / Azure / Google) platforms and related AI services.


• Experience working with search engines, vector databases, or graph databases, such as Elasticsearch / OpenSearch / Solr / Neo4j


• Experience evaluating LLM outputs and performance and RAG infrastructure.


• Understanding of the data science lifecycle, including feature engineering, model training, and evaluation methodologies.


• Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or similar tools.


• Experience with large-scale data processing frameworks such as spark