Senior MLOps (AI/ML)

Location: Amsterdam, Netherlands

Salary: €53,800–€89,900 per year.

Company

hirify.global provides information, analytics, research platforms, healthcare education, and clinical practice solutions.

What you will do

• Bridge Data Science and Engineering by turning experimental NLP, information retrieval, recommendation, and Generative AI models into secure, reliable, scalable production services.
• Automate and orchestrate ML workflows across AWS, Azure, Databricks, foundation model APIs, SageMaker, MLflow, and Azure ML.
• Build and manage model registries, artifact stores, ML CI/CD, data validation, model testing, deployment, and custom SageMaker pipelines.
• Design GAR/RAG components including query interpretation, reflection, chunking, embeddings, hybrid retrieval, semantic search, prompt libraries, guardrails, and structured LLM output.
• Implement pipelines using Elasticsearch, OpenSearch, Solr, vector databases, and graph databases, including knowledge-graph-aware retrieval.
• Build evaluation pipelines for IR metrics, LLM quality, and A/B testing; optimize infrastructure costs and collaborate with subject-matter experts, product managers, data scientists, Responsible AI experts, and Operations Engineers.

Requirements

• 3–5+ years of experience in ML Engineering, MLOps platforms, or shipping ML, search, or GenAI systems to production.
• Strong Python, Java, and/or Scala engineering skills.
• Experience with statistical analysis, machine learning theory, natural language processing, and the Data Science Life Cycle, including feature engineering, model training, and evaluation metrics.
• Hands-on experience with major cloud vendors, including AWS, Azure, and/or Google.
• Experience with search, vector, and graph technologies such as Elasticsearch, OpenSearch, Solr, and Neo4j.
• Experience evaluating LLM models and familiarity with ML frameworks such as PyTorch, TensorFlow, and PySpark.
• Background in scholarly publishing workflows, bibliometrics, or citation graphs.
• Experience with large-scale data processing systems such as Spark.

Culture & Benefits

• Flexible working hours that allow adjustment of working times during the day.
• Focus on work-life balance, trust, respect, collaboration, agility, and quality.
• Wellbeing initiatives, shared parental leave, study assistance, and sabbaticals.
• Country-specific benefits and coverage under the Collective Labor Agreement Publishing Industry.

Hiring process

• Reasonable accommodations are available during the hiring process through the Applicant Request Support Form or by contacting the listed support number.