ML Ops Engineer - Scale Production ML Pipelines

Hiscox; York and North Yorkshire; On-site; GBP 65,000 - 90,000; Full time

Job summary

Hiscox in the United Kingdom is seeking an experienced Machine Learning Engineer to join the newly formed ML Engineering team. You will develop and maintain infra to deploy data science models, build Python APIs, and ensure scalable, production-grade ML solutions across Azure and AWS.

You’ll collaborate with Data Scientists, Platform Engineers and Developers, work in an Agile environment, implement CI/CD, monitor services, and contribute to model registry and lifecycle management to support

Qualifications

• Bachelor's or master's degree in a quantitative field.
• 3-5 years as an ML engineer.
• Experience deploying ML models to production.
• Strong Python development skills.
• Solid experience with cloud platforms (GCP/AWS/Azure).
• Familiarity with Docker and Kubernetes.
• Experience with CI/CD and IaC tools.
• Agile methodologies experience.

Responsibilities

• Develop and maintain ML infrastructure for real-time and batch deployments.
• Build Python APIs (Flask/FastAPI) to serve ML models.
• Collaborate with data scientists and engineers for scalable deployments.
• Design CI/CD pipelines for ML model deployment.
• Monitor, test, and maintain ML services in production.
• Implement model registry improvements and governance.
• Work in Agile teams and participate in iterative development.

Skills

Python development

ML model deployment

Cloud platforms (GCP/AWS/Azure)

Docker

Kubernetes

CI/CD tooling

Agile methodologies

Unit testing

Education

Bachelor's/Master's degree in quantitative field

Tools

Flask/FastAPI

Terraform

Git-based workflows

GitHub Actions

REST APIs

Job description

Hiscox in the United Kingdom is seeking an experienced Machine Learning Engineer to join the newly formed ML Engineering team. You will develop and maintain infra to deploy data science models, build Python APIs, and ensure scalable, production-grade ML solutions across Azure and AWS.

You’ll collaborate with Data Scientists, Platform Engineers and Developers, work in an Agile environment, implement CI/CD, monitor services, and contribute to model registry and lifecycle management to support