Optimove MLOps Engineering Team Leader 

United Kingdom, Scotland 

228554748

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).