Machine Learning Engineer - Utilities in London
Machine Learning Engineer - Utilities

Machine Learning Engineer - Utilities in London

London Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and improve ML features for live energy systems, collaborating with product managers and engineers.
  • Company: Join Kraken, a tech company transforming the energy industry for a sustainable future.
  • Benefits: Flexible hybrid working, competitive salary, and a supportive culture focused on growth.
  • Why this job: Make a real impact in shaping a smarter, greener energy system while developing your skills.
  • Qualifications: Solid foundation in ML, strong Python and SQL experience, and a collaborative mindset.
  • Other info: Exciting challenges await in a dynamic environment with excellent career growth opportunities.

The predicted salary is between 36000 - 60000 £ per year.

Help us use technology to make a big green dent in the universe! Kraken powers some of the most innovative global developments in energy. We’re a technology company focused on creating a smart, sustainable energy system. From optimising renewable generation, creating a more intelligent grid and enabling utilities to provide excellent customer experiences, our operating system for energy is transforming the industry around the world in a way that benefits everyone. It’s a really exciting time in energy. Help us make a real impact on shaping a better, more sustainable future.

This is a hands-on, delivery-focused ML engineering role. You’ll join a team working on mature, live products where the priority is shipping, improving, and maintaining features. While the role is ML-focused, our ML engineers work very close to the software layer so being comfortable with production Python code, databases, and systems is essential. You’ll initially focus on the Companion product, a RAG based chatbot, supporting feature delivery, maintenance, and incremental improvements, while collaborating closely with product managers and engineers across Kraken.

What you'll do:

  • Design, build, and improve machine learning and GenAI-powered features used in live production systems
  • Deliver consistent, high-quality work each sprint (typically 2–3 smaller tickets or 1 larger piece of work per two-week sprint)
  • Work with product managers to clarify requirements and translate them into robust technical solutions
  • Write clean, maintainable Python code and contribute to shared codebases used across ML teams
  • Analyse data, evaluate approaches, and iterate on solutions based on real-world usage
  • Collaborate with other ML engineers and software engineers across Kraken when working on shared systems
  • Ask questions early, seek clarification when needed, and contribute ideas during team discussions
  • Participate in sprint planning, stand-ups, and knowledge-sharing sessions

While our current products are largely GenAI-based and do not train models, a strong grounding in ML fundamentals is still important as the platform continues to evolve.

What you'll need:

  • A solid foundation in machine learning fundamentals, including data analysis, model evaluation, and ML pipelines
  • Strong experience with Python and SQL in a production environment
  • Comfort working in software-engineering-heavy ML roles (this is not a research-only position)
  • Experience working with real-world systems where reliability, readability, and maintainability matter
  • Confidence asking questions, collaborating across teams, and explaining your thinking
  • Ability to work independently on defined tasks and see them through to completion

Experience with the following is a bonus:

  • Exposure to GenAI / LLM-based systems (e.g. prompting, orchestration, evaluation)
  • Familiarity with cloud environments (especially AWS)
  • Experience with tools such as Databricks, Datadog, or similar data / observability platforms
  • Awareness of ML libraries such as PyTorch, TensorFlow, or Hugging Face (even if not used day-to-day)

Ways of working:

  • Two-week sprints with planning and retrospectives
  • Asynchronous-first communication with daily stand-ups
  • Regular knowledge-sharing sessions
  • A no-blame culture with high trust and autonomy
  • Flexible hybrid working, with in-person collaboration typically on Tuesdays and Thursdays

We would prefer someone who can work in our London office on a hybrid remote policy of 1-2 days a week onsite. You do need to be able to work in the UK.

We're very excited to be growing our team. We're looking for skills and experience to help shape and define the future of not only our team, but the wider business at a global scale. If you're reading this and grinning, please apply! There are huge challenges to tackle, and we need amazing people who are keen to get stuck in.

Kraken is a certified Great Place to Work in France, Germany, Spain, Japan and Australia. In the UK we are one of the Best Workplaces on Glassdoor with a score of 4.7. Check out our Welcome to the Jungle site to learn more about our teams and culture.

Are you ready for a career with us? We want to ensure you have all the tools and environment you need to unleash your potential. If you have any specific accommodations or a unique preference, please contact us and we'll do what we can to customise your interview process for comfort and maximum magic!

Machine Learning Engineer - Utilities in London employer: Kraken Digital Asset Exchange

At Kraken, we are committed to fostering a dynamic and inclusive work environment that empowers our employees to thrive. As a Machine Learning Engineer in our London office, you'll be part of a forward-thinking team dedicated to transforming the energy sector through innovative technology. With flexible hybrid working options, a strong focus on collaboration, and a culture that prioritises trust and autonomy, we offer exceptional growth opportunities and the chance to make a meaningful impact on a sustainable future.
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Contact Detail:

Kraken Digital Asset Exchange Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer - Utilities in London

✨Tip Number 1

Get to know the company inside out! Research Kraken's projects and values, especially around sustainability and innovation in energy. This will help you tailor your conversations and show that you're genuinely interested in making a difference.

✨Tip Number 2

Practice your technical skills before the interview. Brush up on Python and SQL, and be ready to discuss your experience with machine learning fundamentals. We want to see how you can apply your knowledge to real-world problems!

✨Tip Number 3

Don’t shy away from asking questions during the interview! It shows your curiosity and willingness to collaborate. Plus, it’s a great way to gauge if the team dynamics fit what you’re looking for.

✨Tip Number 4

Apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, you’ll find all the latest updates about our team and culture there.

We think you need these skills to ace Machine Learning Engineer - Utilities in London

Machine Learning Fundamentals
Data Analysis
Model Evaluation
ML Pipelines
Python
SQL
Software Engineering
Collaboration Skills
Problem-Solving Skills
GenAI / LLM Exposure
Cloud Environments (AWS)
Databricks
Datadog
ML Libraries (PyTorch, TensorFlow, Hugging Face)

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with machine learning and Python. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!

Show Your Passion for Sustainability: Since we’re all about making a green impact, let your enthusiasm for sustainable energy shine through in your application. Share any personal projects or experiences that demonstrate your commitment to this cause.

Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon and focus on what makes you a great fit for the Machine Learning Engineer role.

Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!

How to prepare for a job interview at Kraken Digital Asset Exchange

✨Know Your ML Fundamentals

Brush up on your machine learning fundamentals, especially data analysis and model evaluation. Be ready to discuss how these concepts apply to real-world systems, as this role is all about practical implementation.

✨Showcase Your Python Skills

Since the role requires strong experience with Python, prepare to demonstrate your coding skills. You might be asked to solve a problem or explain your thought process while writing clean, maintainable code.

✨Understand the Product

Familiarise yourself with Kraken's Companion product and its features. Being able to discuss how you would improve or maintain it will show your genuine interest and understanding of the company's goals.

✨Ask Questions and Collaborate

During the interview, don’t hesitate to ask questions. This shows your confidence and willingness to collaborate. Discussing how you would work with product managers and other engineers can highlight your teamwork skills.

Machine Learning Engineer - Utilities in London
Kraken Digital Asset Exchange
Location: London
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