DevOps Engineer

August 27

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Description

• Design, deploy, and manage scalable and reliable cloud infrastructure on a public cloud provider platform (e.g., AWS, GCP) to support our data-intensive applications and machine learning workflows. • Implement and maintain CI/CD pipelines for automated build, test, and deployment processes to ensure fast and efficient delivery of software updates and model deployments. • Develop and maintain monitoring, logging, and alerting systems to proactively identify and address performance issues, security vulnerabilities, and other operational concerns. • Collaborate with cross-functional teams (inc. machine learning and computer vision engineers) to optimize application performance, troubleshoot issues, and ensure high availability and uptime in accordance with SLAs. • Implement and enforce security best practices and compliance standards (e.g. Cyber Essentials, SOC2) to safeguard sensitive data and protect against potential threats and attacks. • Drive continuous improvement initiatives to optimize infrastructure costs, increase operational efficiency, and enhance overall reliability and performance. • Stay updated on emerging technologies, trends, and best practices in DevOps and MLOps to recommend and implement innovative solutions that drive business value.

Requirements

• Proven experience as a DevOps Engineer, Site Reliability Engineer (SRE), or similar role, with a focus on cloud infrastructure and automation. • Strong proficiency in at least one cloud platform (AWS preferable) and hands-on experience with infrastructure as code (IaC) tools such as Terraform, CloudFormation, or equivalent. • Experience with containerization technologies (e.g., Docker). • Solid understanding of CI/CD concepts and experience with CI/CD tools (e.g., Github Actions) for automating software delivery pipelines. • Familiarity with machine learning concepts and frameworks (e.g. PyTorch, TensorFlow) and experience deploying and managing machine learning models in GPU production environments is a plus (e.g. BentoML, Valohai). • Experience with container orchestration platforms (e.g. Kubernetes) for deploying and managing services-based applications. • Strong problem-solving skills, attention to detail, and excellent communication and interpersonal skills. • Right to work in UK

Benefits

• Hybrid work style - ability to work from home and the London office (at least 2 days per week in the office) • Flexible working hours • Equity options • 34 days annual leave (incl. public holidays in your residence country) • Bi-annual company retreat and bi-annual team meetings (workation) • Private medical insurance, including mental health, dental, opticians cover, and business as well as personal travel insurance. • Pension Plans • Cycle to Work Scheme