Mlops Engineer

Harnham
united kingdom of great britain and northern ireland, uk
6 months ago
Applications closed

Related Jobs

View all jobs

AI MLOps Engineer

Morson Edge Peninsula, London, United Kingdom
£600 – £650 pd Remote

Senior Machine Learning Data Scientist - Credit Risk

Martin Veasey Talent Solutions Northampton, Northamptonshire, United Kingdom
£80,000 – £120,000 pa Hybrid

Software Development Engineer, Advertising

Amazon London, United Kingdom
On-site

ML Engineer

Data Idols Farringdon, Greater London, London, EC1M 4BJ, United Kingdom
£60,000 – £65,000 pa Hybrid

Platform Engineer

Faculty AI London, United Kingdom
Hybrid

ML Engineer

Randstad Technologies Recruitment London, City And County Of the City Of London, United Kingdom
£450 – £500 pd Hybrid
Posted
25 Nov 2025 (6 months ago)

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 frequent model releases.

Performance Engineering: Profile and optimise large-scale Spark/Python codebases for production efficiency, focusing on minimising latency and cost.

Knowledge Transfer: 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

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Machine Learning Jobs UK 2026: What to Expect Over the Next 3 Years

Machine Learning Jobs UK 2026: roles, salaries and the MLOps, LLM and generative AI hiring trends shaping UK ML careers over the next three years. Machine learning has undergone a transformation that few technology disciplines can match. In the space of three years it has moved from a specialism sitting at the edges of most organisations' technology strategies to a capability that sits at the centre of them. The tools have changed, the expectations have shifted, and the range of industries treating machine learning as a core business function — rather than an experimental one — has expanded dramatically. For job seekers, this creates both opportunity and complexity in roughly equal measure. The machine learning jobs market of 2026 is significantly larger than it was three years ago, but it is also significantly more demanding. Employers have developed more sophisticated expectations, the technical bar for specialist roles has risen, and the landscape of tools, frameworks, and architectural patterns that practitioners are expected to know has broadened considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what machine learning engineers and researchers are expected to build, and how the definition of a machine learning career is evolving beyond the model-building core toward a much wider range of roles across the full ML lifecycle. This article breaks down what the UK machine learning jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.