Machine Learning Engineer - Utilities
Machine Learning Engineer - Utilities

Machine Learning Engineer - Utilities

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

  • Tasks: Design and improve machine learning features for live production systems in a dynamic team.
  • Company: Join Kraken, a leading tech company transforming the energy sector sustainably.
  • Benefits: Enjoy flexible hybrid working, competitive salary, and a supportive culture.
  • Why this job: Make a real impact on sustainable energy while developing cutting-edge technology.
  • Qualifications: Strong foundation in machine learning, Python, and SQL; teamwork and problem-solving skills.
  • Other info: Be part of a rapidly growing team with excellent career development 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.

Kraken Utilities Our tech platform ‘Kraken’ is already licensed to support 55 million customer accounts globally, and we aim to serve 100 million by 2027. Kraken is the most AI-driven, innovative, forward-thinking platform for energy management. From optimising resources to delivering cost-effective, exceptional customer experiences through advanced Customer Information Systems (CIS), billing, meter data management, CRM, and AI-driven communications.

We’re now charging the Kraken platform to other utility industries (Water and Broadband) and have created a new team called Kraken Utilities. Over the last 3 years we have built this team from scratch to re-architect, design, and develop our Kraken software platform to solve complex industry wide problems within the water and broadband sectors (such as customer experience & water leak detection). The Kraken Utilities team is in a very exciting growth phase, and has already signed six key clients: Severn Trent, Leep, Portsmouth Water, Essential Energy, TalkTalk, and Cuckoo. We are currently 120+ people strong globally.

The role 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 (FR/EN) 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 at inclusion@kraken.tech and we’ll do what we can to customise your interview process for comfort and maximum magic!

Studies have shown that some groups of people, like women, are less likely to apply to a role unless they meet 100% of the job requirements. Whoever you are, if you like one of our jobs, we encourage you to apply as you might just be the candidate we hire. Across Kraken, we’re looking for genuinely decent people who are honest and empathetic. Our people are our strongest asset and the unique skills and perspectives people bring to the team are the driving force of our success.

As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. We consider all applicants without regard to race, colour, religion, national origin, age, sex, gender identity or expression, sexual orientation, marital or veteran status, disability, or any other legally protected status.

Our (i) Applicant and Candidate Privacy Notice and Artificial Intelligence (AI) Notice, (ii) Website Privacy Notice and (iii) Cookie Notice govern the collection and use of your personal data in connection with your application and use of our website. These policies explain how we handle your data and outline your rights under applicable laws, including, but not limited to, the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Depending on your location, you may have the right to access, correct, or delete your information, object to processing, or withdraw consent. By applying, you acknowledge that you’ve read, understood and consent to these terms.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Machine Learning Engineer - Utilities employer: Kraken

At Kraken, we are committed to fostering a dynamic and inclusive work environment where innovation thrives. As a Machine Learning Engineer in our London office, you'll be part of a rapidly growing team dedicated to transforming the energy sector through cutting-edge technology. We offer flexible hybrid working arrangements, a strong focus on employee development, and a culture that values collaboration and creativity, making us an exceptional employer for those looking to make a meaningful impact in the world of sustainable energy.
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Contact Detail:

Kraken Recruiting Team

StudySmarter Expert Advice 🤫

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

✨Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current Kraken employees on LinkedIn. A friendly chat can sometimes lead to opportunities that aren’t even advertised!

✨Tip Number 2

Show off your skills! Create a portfolio showcasing your machine learning projects or contributions to open-source. This gives us a tangible way to see what you can do and how you think.

✨Tip Number 3

Prepare for the interview by brushing up on your Python and SQL skills. We love candidates who can demonstrate their technical prowess, so be ready to tackle some coding challenges during the process.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Kraken.

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

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

Some tips for your application 🫡

Show Your Passion for Sustainability: When writing your application, let your enthusiasm for sustainable energy shine through! We want to see how your skills can help us make a big green dent in the universe. Share any relevant projects or experiences that highlight your commitment to this cause.

Tailor Your Experience: Make sure to align your experience with the job description. Highlight your hands-on ML engineering work and any experience with Python and SQL. We love seeing how your background fits into our mission at Kraken, so don’t hold back!

Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your skills and experiences. We appreciate well-structured applications that make it easy for us to see why you’d be a great fit for the team.

Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values.

How to prepare for a job interview at Kraken

✨Know Your ML Fundamentals

Brush up on your machine learning basics, especially data analysis and model evaluation. Being able to discuss these concepts confidently will show that you have a solid foundation, which is crucial for the role.

✨Showcase Your Python Skills

Prepare to demonstrate your Python coding abilities. Be ready to discuss past projects where you've written clean, maintainable code, and how you've used it in production environments. This will highlight your technical fit for the position.

✨Understand the Kraken Platform

Familiarise yourself with Kraken's technology and its applications in energy management. Knowing how the platform operates and its impact on customer experience will help you align your answers with the company's goals during the interview.

✨Ask Thoughtful Questions

Prepare insightful questions about the team dynamics, project expectations, and the future of the Kraken Utilities team. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.

Machine Learning Engineer - Utilities
Kraken

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