MLOps Engineer (GCP)

Location: York, United Kingdom

Company

hirify.global is an insurance company with a Group and Enterprise Services team responsible for the lifecycle of approximately 140 applications.

What you will do

• Lead, recruit, onboard, coach, and mentor ML Engineers while identifying team capacity and capability gaps.
• Own the deployment framework for data science services and oversee data flow from the business data warehouse into the ML lifecycle.
• Build and maintain infrastructure for real-time and batch ML model deployment in GCP Vertex AI and other cloud environments.
• Develop Python APIs with Flask or FastAPI, CI/CD pipelines, model registries, monitoring, and automation for dataset build, training, evaluation, deployment, and model upgrades.
• Influence architecture and solution design, breaking business requirements into deliverable work and milestones and moving proof-of-concepts to production-ready platforms.
• Collaborate with data scientists, data engineers, platform engineers, developers, and other technical teams to improve reliability, scalability, performance, and analytics maturity.

Requirements

• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or Engineering, or equivalent experience.
• 5+ years of experience as an ML Engineer.
• Strong understanding of data science principles and the challenges of migrating research code into production code.
• Hands-on GCP and ML engineering experience, including deploying, monitoring, and maintaining production ML models such as neural networks and random forests; Vertex AI is essential.
• Solid Python development experience in an ML engineering context, including Flask or FastAPI, object-oriented programming, unit testing, and TDD.
• Strong software engineering best practices, problem-solving, independent technical execution, and ability to articulate approaches to quality, stability, performance, scalability, deployment, security, maintenance, and documentation.
• Experience with infrastructure as code tools such as Terraform, cloud platforms, containerization with Docker, deployment orchestration, CI/CD tools, Git-based workflows, API monitoring, and logging.
• Familiarity with Agile methodologies and experience working in Agile teams.
• Ability to work in a small team within a larger product division, communicate and present effectively, and operate in a rapidly changing, fast-paced environment.

Nice to have

• Experience with Azure.
• Experience in financial services or highly regulated insurance environments.

Culture & Benefits

• Permanent, full-time employment.
• Work within an Agile, collaborative, and cross-disciplinary environment.
• Contribute to a culture focused on innovation, automation, quality, and continuous improvement.
• Work as part of the Data service vertical within Group and Enterprise Services.