Machine Learning Engineer

What you’ll do

• Take ML and GenAI solutions from prototype to production: deployment, monitoring, scaling.
• Build and maintain CI/CD and MLOps pipelines (training, versioning, model serving).
• Deploy LLM-based applications (RAG, agents, API integrations) on cloud infrastructure.
• Manage cloud infrastructure for AI workloads with infrastructure-as-code.
• Work directly with the client’s data and engineering teams.

Must have

• 3+ years in MLOps, ML engineering, or DevOps for ML workloads.
• Hands-on cloud ops and deployment (AWS, Azure, or GCP).
• Docker, Kubernetes, CI/CD; Terraform or similar IaC.
• Python; experience with MLflow, Kubeflow, SageMaker / Azure ML or similar.
• Practical experience with GenAI/LLM apps in production (RAG, vector databases, LLM APIs).
• Based in the EU, able to work CET hours.
• English: upper-intermediate or higher.

Nice to have

• Experience in regulated industries (pharma, life sciences, finance).
• Monitoring and observability for ML/LLM systems, cost optimisation.

Terms

• Freelance/B2B contract directly with the Customer, 12 months, full-time.
• Budget up to €45-50k/year, depending on experience.
• Remote within the EU
• Start ASAP.

To apply: send your CV, or a LinkedIn link, with 2–3 lines about an ML/GenAI system you took to production.

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