2 months ago
London, United KingdomSenior
Responsibilities
- Build robust, secure, and scalable cloud infrastructure for AI and ML workflows.
- Partner with technical and non-technical stakeholders from idea generation through implementation and shipping.
- Enable Machine Learning Engineers and Data Scientists through internal best practices, standards, and reusable code repositories.
- Identify ways customers can leverage cloud infrastructure to solve key challenges.
- Create and maintain reusable company-wide libraries and infrastructure-as-code.
- Research and integrate open-source technologies to improve Faculty’s infrastructure capabilities.
- Handle customer requirements gathering, technical planning, and project scoping.
Requirements
- Deep experience with both Azure and AWS.
- Strong experience with Infrastructure as Code, especially Terraform.
- Experience building and deploying containerized solutions using Docker and Kubernetes.
- Strong CI/CD and GitOps practices.
- Proficient knowledge of networking and cloud security.
- Ability to work directly with clients and stakeholders on requirements, technical planning, and scoping.
- Pragmatic, outcome-focused approach with the ability to execute complex projects.
- Scientific, evidence-based approach to testing assumptions and improving practices.
Benefits
- The company is open to conversations about part-time hours.
- The interview process includes a talent team screen, pair programming interview, system design interview, and commercial interview.
- Applicants may use AI for research and interview preparation, but not to generate answers during live interviews; an AI note-taker is used in interviews with an opt-out available.
