Senior Dev/ML Ops Engineer

Skills

About the Role

You will manage ML models and core infrastructure from development through deployment, monitoring, and improvement. You will build CI/CD pipelines, automate deployment and orchestration, maintain secure and observable systems, troubleshoot performance issues, collaborate on ML-powered features, and document operational workflows.

Requirements

• Senior-level DevOps, MLOps, or infrastructure engineering experience
• Python
• TensorFlow or PyTorch
• AWS, GCP, or Azure
• Docker
• Kubernetes
• CI/CD systems, including GitHub Actions, GitLab CI, or ArgoCD
• Infrastructure as code, including Terraform or Helm
• Data engineering concepts, including ETL pipelines, data lakes, and batch or stream processing
• Distributed systems debugging
• Security and compliance best practices for software and ML systems

Responsibilities

• Manage the lifecycle of ML models and core infrastructure
• Build and maintain CI/CD pipelines for software and ML workflows
• Ensure production systems and ML infrastructure are reliable, scalable, observable, and secure
• Automate deployment, orchestration, and environment management
• Collaborate to bring ML-powered features to production
• Detect, troubleshoot, and resolve infrastructure and model performance issues
• Document infrastructure, workflows, and operational procedures

Benefits

• 23 days of annual leave
• 15 days of paid sick leave
• Paid company holidays
• Fully funded private healthcare for UK employees
• Equity
• Pension scheme with 8% total contribution
• Free daily breakfast, catered lunch, and snacks