MLOPs Engineer

Harnham; Manchester; Hybrid; GBP 100,000 - 125,000; Full time

Job summary

A leading global e-commerce client in Manchester is seeking an experienced MLOps Engineer to drive operational excellence within their data function. The role involves designing and deploying end-to-end MLOps processes, architecting solutions for real-time model serving, and mentoring a large team. The ideal candidate has proven MLOps experience, expertise in Databricks, and strong skills in Apache Spark and Python. This position offers flexibility for remote work and competitive remuneration.

Qualifications

• Proven experience designing and implementing end-to-end MLOps processes in a production environment.
• Expert proficiency with Databricks and MLflow.
• Strong experience with GIT for version control and building CI/CD/release pipelines.

Responsibilities

• Design and deploy end-to-end MLOps processes, focusing on governance and automation.
• Lead the integration and use of MLflow for model registry and deployment.
• Build and automate CI/CD pipelines for reliable model releases.

Skills

MLOps

Databricks

Apache Spark

Python

SQL

GIT

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:

• Design and deploy end‑to‑end MLOps processes, focusing heavily on governance, reproducibility, and automation.
• Architect and implement solutions to transition high‑volume model serving (10M+ customers, 1.2M+ product variants) to real‑time performance.
• Lead the optimal integration and use of MLflow for model registry, experiment tracking, and deployment within the Databricks platform.
• Build and automate robust CI/CD pipelines using GIT to ensure stable, reliable, and frequent model releases.
• Profile and optimise large‑scale Spark / Python codebases for production efficiency, focusing on minimising latency and cost.
• Act as the technical lead to embed MLOps standards into the core Data Engineering team.

Key Skills: Must Have:

• MLOps – proven experience designing and implementing end‑to‑end MLOps processes in a production environment.
• Cloud ML Stack – expert proficiency with Databricks and MLflow.
• Big Data / Coding – expert Apache Spark and Python engineering experience on large datasets.
• Core Engineering – strong experience with GIT for version control and building CI/CD/release pipelines.
• Data Fundamentals – excellent SQL skills.

Nice-to-Have / Desirable Skills:

• DevOps / CICD (Pipeline experience)
• GCP (Familiarity with Google Cloud Platform)
• Data Science (Good understanding of math / model fundamentals for optimisation)
• Familiarity with low‑latency data stores (e.g., CosmosDB).

If you have the capability to bring MLOps maturity to a traditional Engineering team using the MLFlow / Databricks / Spark stack, please email : with your CV and contract details.

Desired Skills and Experience

• MLOPS
• GIT
• MLFlow
• Spark
• Python
• SQL
• GCP
• DevOps
• CICD