Lead ML Ops Engineer — Production AI Platform (Hybrid)

Artificial Intelligence Jobs; Greater London; Hybrid; GBP 75,000 - 85,000; Full time

Benefits offered by this job

Annual bonus (10%)

Job summary

Artificial Intelligence Jobs in London is seeking a Senior ML Ops Engineer to own the infrastructure, deployment, and operational excellence of production ML systems in a hybrid setup (1-2 days per week). You will design production-grade ML orchestration pipelines, deploy and monitor models, build cloud-native infra with Kubernetes, and drive CI/CD and observability to scale AI services.

You will work with Dagster, Airflow, or Prefect, use Terraform or Bicep, and collaborate with data scientists

Qualifications

• Strong Python software engineering experience.
• Experience deploying ML infrastructure in production.
• Knowledge of orchestration tools (Dagster/Airflow/Prefect).
• Hands-on with Kubernetes and containerised workloads.
• IaC experience (Terraform/Bicep/Pulumi).
• Experience building CI/CD pipelines and monitoring/observability.
• Cloud experience, ideally Azure.
• Exposure to LLMs, NLP, or generative AI.

Responsibilities

• Own and evolve infrastructure powering AI/ML services.
• Design, build, and maintain production-grade ML orchestration pipelines (Dagster, Airflow, Prefect).
• Deploy, monitor, and scale ML models and LLM-powered solutions.
• Build cloud-native infrastructure with Kubernetes and IaC (Terraform/Bicep).
• Develop robust CI/CD and observability frameworks for ML operations.
• Collaborate with Data Scientists, software engineers, and client teams to deliver scalable AI solutions.
• Influence technical standards and future direction of the AI platform.

Skills

Python

ML Ops

Kubernetes

CI/CD

Observability

Azure

LLMs

IaC

Tools

Dagster

Airflow

Prefect

Terraform

Bicep

Pulumi

Job description

Artificial Intelligence Jobs in London is seeking a Senior ML Ops Engineer to own the infrastructure, deployment, and operational excellence of production ML systems in a hybrid setup (1-2 days per week). You will design production-grade ML orchestration pipelines, deploy and monitor models, build cloud-native infra with Kubernetes, and drive CI/CD and observability to scale AI services.

You will work with Dagster, Airflow, or Prefect, use Terraform or Bicep, and collaborate with data scientists