Senior Machine Learning Engineer

Stark Danmark A/S
Gildersome
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer (Azure Synapse) - London

Senior Electronics Engineer

Senior Data Science Consultant, Customer Data & Technology

Senior and Mid Level Data Engineers

Senior and Mid Level Data Engineers

Senior Data Analyst - Pricing Data Engineering & Automation, CUO Global Pricing

Senior Machine Learning Engineer

Apply remote type: Homeworking only

Locations: Home-Based England

Time type: Full time

Posted on: Posted 3 Days Ago

Time left to apply: End Date: January 28, 2025 (30+ days left to apply)

Stark Groupis hiring now for aSenior Machine Learning Engineerworking from home (remote – UK based).

Stark, a leading building materials distributor in Northern Europe, is looking for aSenior Machine Learning Engineerwho is 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:

  • Play a lead role in the design and development of overall AI systems using data science and software engineering best practices 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.
  • Write production grade Python and SQL for feature engineering and model pipelines, incorporating best practices such as packaging, unit testing, version control, and logging to 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.
  • Contribute to and improve overall team standards and best practices to enhance the quality and efficiency of how the team operates and our outputs.
  • Lead on collaborative knowledge sharing and improvements to working practices 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 ofSTARK Building Materials UKand 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!

What's next…

If your application is successful, our in-house recruitment team will be in touch to arrange an interview and to answer any initial questions you have.

Where a role is advertised as full-time, we are open to discussing part-time and job share options during the application process. If you require additional support as part of the application and interview process, we are happy to provide reasonable adjustments to help you to be at your best.

Stark Building Materials UK is a Ban the Box employer and will consider the suitability of applicants with criminal convictions on a case-by-case basis.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.