Senior MLOps Engineer: Kubernetes & AI Platform Lead

Harnham; Greater London; Hybrid; GBP 75,000 - 85,000; Full time

Benefits offered by this job

Private healthcare

Job summary

Harnham in London is seeking a Senior MLOps Engineer to own the infrastructure, deployment and orchestration for production ML services. This hands-on role offers significant influence over platform direction and engineering standards.

You will build and maintain orchestration pipelines with Dagster, Airflow or Prefect, deploy workloads in Kubernetes, and drive CI/CD and IaC best practices. Collaboration with software engineers, ML engineers and data scientists is essential.

Qualifications

• Strong Python software engineering experience.
• Hands-on MLOps or platform engineering background.
• Experience with ML workflow orchestration tools.
• Production Kubernetes expertise.
• Infrastructure-as-code experience, ideally Terraform or Bicep.
• Knowledge of monitoring, logging and deployment best practices.
• Exposure to Azure and production ML environments is beneficial.

Responsibilities

• Own and develop the infrastructure supporting AI and ML services.
• Build and maintain orchestration pipelines using tools such as Dagster, Airflow or Prefect.
• Deploy, manage and optimise workloads in Kubernetes environments.
• Improve monitoring, observability and platform reliability.
• Implement infrastructure-as-code and CI/CD best practices.
• Partner with software engineers, ML engineers and data scientists to deliver scalable solutions.

Skills

Python

MLOps

Orchestration tools

Kubernetes

Infrastructure as Code

Monitoring & logging

Azure exposure

Tools

Dagster

Airflow

Prefect

Job description

Harnham in London is seeking a Senior MLOps Engineer to own the infrastructure, deployment and orchestration for production ML services. This hands-on role offers significant influence over platform direction and engineering standards.

You will build and maintain orchestration pipelines with Dagster, Airflow or Prefect, deploy workloads in Kubernetes, and drive CI/CD and IaC best practices. Collaboration with software engineers, ML engineers and data scientists is essential.