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DevOps Engineer – Reinforcement Learning Platforms
We are seeking an experienced DevOps Engineer to help build and scale a web-based platform for reinforcement learning (RL) training and RLOps. You will design, implement, and maintain the cloud infrastructure, CI/CD pipelines, and deployment systems that support large-scale RL workloads.
Responsibilities
• Design and manage scalable cloud infrastructure for high-performance RL training and distributed environments
• Build and optimise CI/CD pipelines for open-source and enterprise components
• Implement containerisation and orchestration using Docker and Kubernetes
• Develop Infrastructure as Code solutions (Terraform, CloudFormation, Pulumi)
• Implement monitoring, logging, and alerting for distributed ML systems
• Collaborate with ML teams on resource optimisation and cost efficiency
• Apply security best practices, manage access controls, and ensure compliance
• Automate operational tasks: backups, disaster recovery, maintenance
• Support GPU clusters and distributed compute resources for RL workloads
• Maintain availability and performance of production ML systems
Requirements
• Degree in Computer Science/Engineering or 3+ years of DevOps/infrastructure experience
• Strong background with AWS, GCP, or Azure, including ML/AI workloads
• Proficiency with Docker, Kubernetes, and ML-focused orchestration
• Experience with Terraform/CloudFormation/Pulumi and configuration management
• Solid understanding of CI/CD tools (GitHub Actions, GitLab CI, Jenkins)
• Knowledge of monitoring/observability tools (Prometheus, Grafana, OpenObserve)
• Experience with GPU infrastructure and distributed ML compute frameworks
• Familiarity with MLOps tools and model lifecycle management
• Strong scripting skills (Python, Bash)
• Understanding of cloud networking, security, and database fundamentals
• Experience with HPC environments or schedulers is a plus
• Strong problem-solving and communication skills
Compensation & Benefits
• Competitive salary and stock options
• 30 days’ holiday plus bank holidays
• Flexible and remote working options
• Enhanced parental leave
• £500 annual learning and development budget
• Pension scheme
• Regular socials and quarterly gatherings
• Bike-to-Work scheme