MLOPs Engineer

Harnham - Data & Analytics Recruitment; City Of London; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading e-commerce firm in the United Kingdom is seeking a Senior MLOps Engineer to drive operational excellence in their data function. The ideal candidate will design end-to-end MLOps processes and transition high-volume model serving to real-time capability. Strong experience in MLflow and Databricks is essential, along with the ability to lead a large engineering team. This position offers flexibility for remote work with competitive compensation outside IR35.

Qualifications

• Proven experience in MLOps processes and governance.
• Experience in transitioning to real-time model serving.
• Strong expertise in MLflow and Databricks for CI/CD.

Responsibilities

• Design and deploy end-to-end MLOps processes.
• Architect solutions for high-volume model serving.
• Lead integration of MLflow within the Databricks platform.

Skills

MLOps Strategy & Implementation

Real-Time Pipeline Build

MLflow mastery

Databricks integration

DevOps for ML

Job description

MLOps Engineer

Outside IR35 - 500-600 Per Day

Ideally, 1 day per week / fortnight in the office, flexibility for remote work for the right candidate.

A market-leading global e-commerce client is urgently seeking a Senior MLOps Lead to establish and drive operational excellence within their largest, most established data function (60+ engineers). This is a mission-critical role focused on scaling their core on-site advertising platform from daily batch processing to real-time capability.

This role suits a hands‑on MLOps expert who is capable of implementing new standards, automating deployment lifecycles, and mentoring a large engineering team on best practices.

What you’ll be doing

• MLOps Strategy & Implementation : Design and deploy end‑to‑end MLOps processes, focusing heavily on governance, reproducibility, and automation.
• Real‑Time Pipeline Build : Architect and implement solutions to transition high‑volume model serving (10M+ customers, 1.2M+ product variants) to real‑time performance.
• MLflow & Databricks Mastery : Lead the optimal integration and use of MLflow for model registry, experiment tracking, and deployment within the Databricks platform.
• DevOps for ML : Build and automate robust CI / CD pipelines using GIT to ensure stable, reliable, and freq…