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MLOps Engineer

Job Description


Paris x2 days a week in office


Xcede are delighted to partner with one of Europe's most exciting HealthTech firms. The organisation is utilising a blend of modern AI expertise & domain specialisation in an effort to link the most talented specialist healthcare professionals with the people and organisations that need their expertise the most.

The automated, intelligence-led features of the company's product are their differentiator, and as a result, their AI & ML unit is realistically their most impactful team.

They're currently growing organically based on demand from their customers, leading to the current search for an MLOps Engineer.


  • Develop and maintain the infrastructure for data generation, model training, and machine learning model deployment pipelines.
  • Collaborate with data scientists and machine learning engineers to design and implement scalable and efficient ML solutions.
  • Implement and manage version control, continuous integration, and continuous deployment systems for ML models and related components.
  • Monitor and optimise ML models and pipelines for performance, scalability, and cost-efficiency.
  • Work closely with DevOps and IT teams to ensure seamless integration of ML components into existing systems and processes.
  • Design and implement monitoring, alerting, and logging systems to track the health and performance of ML models and pipelines.
  • Ensure compliance with data privacy, security, and regulatory requirements throughout the ML development and deployment lifecycle.
  • Troubleshoot and resolve issues related to ML pipelines, infrastructure, and deployments.
  • Stay updated with the latest advancements in ML technologies and practices to continuously improve the efficiency and effectiveness of the ML infrastructure.
  • Collaborate with cross-functional teams to define and implement best practices for ML model development, deployment, and maintenance.


  • BSc/ MSc / PhD degree in Computer Science or STEM subject
  • Demonstratable commercial experience working on MLOps projects
  • Strong Python coding skills (PySpark a bonus too!)
  • Experience with modern development methods and tooling:

  1. containers (e.g., Docker)
  2. container orchestration (Kubernetes / K8s)
  3. CI/CD tools (e.g., Circle CI, Azure DevOps, Jenkins, GitHub actions)
  4. Version control (Git, Github, Gitlab)
  5. Orchestration / DAGs tools (e.g., Argo, Airflow, Kubeflow)

  • Azure / AWS / GCP experience & familiarity


Please register your interest by sending your CV to or click the Apply Link.