DevOps Engineer
Role details
Job location
Tech stack
Job description
- 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
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Degree in Computer Science/Engineering or 3+ years of DevOps/infrastructure experience
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Strong background with AWS, GCP, or Azure, including ML/AI workloads
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Proficiency with Docker, Kubernetes, and ML-focused orchestration
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Experience with Terraform/CloudFormation/Pulumi and configuration management
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Solid understanding of CI/CD tools (GitHub Actions, GitLab CI, Jenkins)
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Knowledge of monitoring/observability tools (Prometheus, Grafana, OpenObserve)
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Experience with GPU infrastructure and distributed ML compute frameworks
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Familiarity with MLOps tools and model lifecycle management
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Strong scripting skills (Python, Bash)
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Understanding of cloud networking, security, and database fundamentals
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Experience with HPC environments or schedulers is a plus
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Strong problem-solving and communication skills Compensation & Benefits, * DevOps
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IaC
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CI/CD tools
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ML/AI
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observability toola
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GPU infrastructure
Benefits & conditions
- Enhanced parental leave
- £500 annual learning and development budget
- Pension scheme
- Regular socials and quarterly gatherings
- Bike-to-Work scheme
