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Optimove MLOps Engineering Team Leader 
United Kingdom, Scotland 
228554748

08.12.2024

Key responsibilities include:

  • Managing and optimising existing ML model deployments to ensure reliability and efficiency.
  • Continuously improving the architecture, processes, and tools used for model deployment, monitoring, and lifecycle management.
  • Collaborating closely with data scientists to understand and implement model requirements.
  • Partnering with R&D teams to align technical strategies and integrate ML solutions into broader systems.
  • Implementing robust CI/CD pipelines, monitoring systems, and infrastructure automation.
  • Upholding best practices in security, cost management, and infrastructure design for cloud environments.

Responsibilities:

  • Lead and mentor the MLOps team
  • Design, implement, and maintain scalable MLOps pipelines.
  • Oversee deployment and monitoring of machine learning models in production.
  • Collaborate with data scientists, product managers, R&D engineers and stakeholders to align on goals and technical strategies.
  • Ensure high availability and performance of deployed ML systems.
  • Define and enforce best practices for CI/CD, infrastructure automation, and model lifecycle management.
  • Manage cloud resources and optimise costs (AWS preferred).

Requirements:

    • Proven experience leading MLOps or software engineering teams.
    • Expertise in Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
    • Deep understanding of CI/CD tools (e.g., AWS CodePipeline, Jenkins, GitLab CI) and infrastructure-as-code (e.g., AWS CloudFormation, Terraform, etc.).
    • Hands-on experience with AWS services such as S3, Lambda, SageMaker, ECS, and CloudWatch.
    • Strong understanding of containerisation (Docker, Kubernetes) and orchestration.
    • Experience with monitoring tools (e.g., Prometheus, Grafana).
    • Excellent problem-solving and leadership skills.
    • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).