DevOps Engineer – Reinforcement Learning Platforms

6 days ago


London Area, United Kingdom Gattaca Full time £80,000 - £120,000 per year

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



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