6 months ago
London, United KingdomSenior
Responsibilities
- Own and maintain deployment and MLOps tooling to improve software delivery quality and reliability.
- Build features for notebook development environments and refine model monitoring systems.
- Design and implement infrastructure-as-code and DevSecOps processes for distributed, containerized microservices.
- Integrate platform services across AWS, Azure, and GCP for global client environments.
- Scale internal enablement capabilities and accelerate machine learning deployment.
- Collaborate with customer-facing technologists and communicate with technical and non-technical peers.
Requirements
- Experience building internal tools and foundational platform systems.
- Understanding of the machine learning product lifecycle and moving models from exploration to production.
- Modern systems programming skills in Python or Go.
- Practical experience with Docker and Kubernetes for distributed systems.
- Infrastructure-as-Code experience with Terraform or CloudFormation.
- Interest in DevSecOps practices and ability to take high levels of ownership.
- Ability to work effectively in small, ambitious teams.
Benefits
- Part-time hours may be discussed.
- The company encourages applications from people of all backgrounds and offers an inclusive recruitment process.
- Candidates may use AI for research and interview preparation, but not to generate answers during live interviews; Metaview AI note-taking is used in interviews and can be declined.
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