National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Machine Learning Engineer

Coventry
7 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer - up to £135k base plus equity

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Stark Group are hiring now for a Senior Machine Learning Engineer working from home (remote - UK based).

Stark a leading building materials distributor in Northern Europe, is looking for a Senior Machine Learning Engineer who's as passionate about great service as we are.

We provide a fulfilling and enjoyable work environment with ample opportunities for career growth, along with a competitive salary, staff discount, life assurance, and 34 days of holiday (inclusive of bank holidays).

What you'll be doing:

You will play a lead role designing, developing and deploying AI solutions on a product basis and work to further the progress of the AI and Advanced Analytics team. This includes setting direction and being responsible for Machine Learning projects, collaborating with other data areas, our partners and the wider business to transform AI prototypes into production and having responsibility for the management and improvement of deployed models and data pipelines.

You will be required to:

Play a lead role in the design and development of overall AI systems using data science and software engineering best practice and techniques to increase profit, decrease cost and optimize workflow of Stark Group.

Work on a range of projects across the business from Supply Chain to Marketing to positively impact financial performance.

Collaborate and direct Data Scientists to turn prototypes into production-grade AI systems, increasing efficiency in the production of outputs and ensuring that the business has the most up-to-date data available upon which to base key decisions.

Writing production grade Python and SQL for feature engineering and model pipelines, incorporating best practices such as packaging, unit testing, version control and logging ensure that the software we deliver is of high quality, extensible and reproducible.

Collaborate with digital areas to ensure interpretability and reliability of AI systems reducing the need for costly manual intervention.

Play a leading role in contributing to and improving overall team standards and best practice to improve the quality and efficiency of how the team operates and our outputs. Innovate to drive best practices for data within Stark through use of new technologies, Machine Learning and AI, bringing other areas along with us.

Lead on collaborative knowledge sharing and improvements to working practices order to further personal development and data science within Stark.

Nurture and develop good working relationships with the team, project stakeholders and customers to ensure smooth product delivery.

What you'll need to have:

MSc in a relevant discipline (e.g. Computer Science, Data Science, Information technology etc.) or relevant experience.

Experience in a hands-on developer role within an AI team.

Previous programming experience with data in Python and SQL, ideally in Software Engineering, Data Engineering or Data Science.

Knowledge and experience of the Python data & AI stack

Knowledge and experience of development and version control tools and workflows (e.g. Git, Feature branch)

Experience of MLOps and associated tools such as Azure DevOps/Github, MLFlow, Azure ML

Experience working with large datasets/big data architectures; particularly Pyspark / Databricks.

Experience deploying container technologies (e.g. Docker, Kubernetes)

Experience playing a lead role on technical AI projects.

Excellent communication skills with both technical and non-technical audiences

High level of accuracy of work and attention to detail.

Ability and desire to self-learn and pick up emerging technologies.

Positive attitude and outlook and enjoy working as part of a team to share knowledge and ideas.

Desirable

Experience of Data & AI with Azure, particularly Azure ML

Experience working with and deploying LLMs

Experience with deploying cloud resources using infrastructure-as-code, particularly Azure/Bicep

What's in it for you:

Discretionary bonus

A wide range of voluntary benefits including holiday buying, discounted gym membership, car salary sacrifice scheme, Cycle2Work, Benenden Healthcare and more.

Access to a wealth of health and wellbeing services including access to online GP appointments and mental health support

Generous employee discounts

Access to discounts with hundreds of your favourite high street and online retailers

Retirement savings plan

Life assurance

Enhanced maternity/paternity/adoption leave for anyone expecting or adopting a child

Why STARK?

We're proud to be part of STARK Building Materials UK and dedicated to providing top-quality products and exceptional service to our customers. We're a friendly and collaborative team, passionate about what we do and committed to doing it well.

If you're ready to take your career to the next level and join a team that is dedicated to providing great service, we want to hear from you. Apply today

National AI Awards 2025

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 to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.