Machine Learning Engineer/Senior Machine Learning Engineer

Datatech Analytics
Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer - Agentic AI Platform

Senior Machine Learning Scientist

Senior Machine Learning Scientist

Machine Learning Engineer / Senior Machine Learning Engineer


Location: Manchester – Hybrid working two days per week on site


Salary: negotiable based on experience


Ref : J13039


This is an exciting opportunity to join a major organisation that is undergoing a large scale transformation within its Pricing and Analytics function. Significant investment is being made in technology, tooling and people development, creating a genuine chance to influence how modern data and analytics products are built and deployed.


The team is expanding and looking for a Machine Learning Engineer or Senior Machine Learning Engineer to design, build and maintain the frameworks, tooling and packages that support high quality modelling and analytical workflows. You will play a key role in enabling fast, reliable and scalable delivery of ML driven solutions across the business.


The environment is collaborative, fast paced and engineering focused, with a strong emphasis on high standards, automation and continuous improvement.


Role

  • Develop and operationalise Python based modelling tools and frameworks that support the full analytical lifecycle
  • Create tools, APIs and processes that enable seamless, efficient and controlled deployment of ML and statistical models
  • Support teams across Pricing and Analytics with standardised modelling approaches and robust engineering practices
  • Help raise engineering maturity across the department through best practice, knowledge sharing and high quality code delivery

Experience

  • Strong experience building data or software products using Python and Git
  • A mindset of continual improvement and a passion for reliable, scalable engineering
  • The ability to collaborate effectively with both technical and non-technical colleagues
  • Experience delivering in a fast moving commercial environment
  • Exposure to regulated industries or personal lines insurance is beneficial but not essential

Applicants must be eligible and authorised to work in the United Kingdom.


If you are driven by building high quality ML tooling, enjoy solving complex engineering challenges and want to contribute to a major transformation, we would be keen to hear from you.


Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift / voucher scheme.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.