Senior Machine Learning Engineer - Utilities
Senior Machine Learning Engineer - Utilities

Senior Machine Learning Engineer - Utilities

Full-Time 48000 - 72000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build AI-powered systems to tackle real-world energy challenges.
  • Company: Join Kraken, a leading tech company revolutionising the energy sector.
  • Benefits: Enjoy competitive pay, flexible working, and opportunities for growth.
  • Why this job: Make a meaningful impact on sustainable energy while advancing your career.
  • Qualifications: Strong ML experience, Python skills, and a passion for innovation.
  • Other info: Be part of a dynamic team with a culture of learning and collaboration.

The predicted salary is between 48000 - 72000 £ 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.

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.

We are building out our Machine Learning & AI capability within Kraken Utilities and are looking for a Senior Machine Learning Engineer to help design, build and scale ML-powered products already running in production. This is a hands-on, product-focused role. While you will bring strong ML fundamentals, the reality of our environment is that ML work is tightly coupled with software engineering, production systems, and real customer use cases. Many of our current products are GenAI-driven rather than model-training heavy, but we value engineers who understand the full ML lifecycle and can apply those skills as our products evolve. You will work closely with product managers, designers, software engineers and other ML practitioners, contribute to technical direction and best practices, and take ownership of complex problems across our suite of AI and ML products.

What you’ll do:

  • Design, build and deploy machine-learning and AI-powered systems that solve real business and customer problems.
  • Work end-to-end: from data exploration and experimentation through to production deployment, monitoring and iteration.
  • Collaborate closely with product managers and engineers to shape solutions that are practical, scalable and maintainable.
  • Lead deep technical investigations into complex or ambiguous problems, including critical bugs across multiple systems. Define and improve ML and engineering best practices within the team.
  • Run and analyse experiments (e.g. A/B tests) to validate product and model improvements.
  • Stay up to date with advances in ML, GenAI and developer tooling, and apply them thoughtfully to our products.
  • Contribute to a culture of learning through knowledge sharing, internal talks and mentoring.

What you’ll need:

  • Strong hands-on experience applying machine learning in production environments (industry or equivalent research experience) with a proven track record of writing maintainable, testable code in complex codebases.
  • Excellent Python skills and solid SQL experience. Deep understanding of ML fundamentals: data analysis, model selection, evaluation, deployment and monitoring.
  • Experience working with ML / data libraries such as pandas, NumPy, scikit-learn, PyTorch or TensorFlow. Comfort working in a software-engineering-heavy environment (version control, CI/CD, code reviews, MLOps principles).
  • Experience building and operating systems on cloud infrastructure (AWS preferred).
  • Ability to clearly explain technical concepts and trade-offs to a wide range of stakeholders.
  • Confidence working autonomously, asking questions early, and collaborating across teams and with clients.

Nice-to-have:

  • Experience building GenAI or NLP-based products.
  • Exposure to LLM tooling, prompting, agents or evaluation techniques.
  • Experience with Kubernetes, dbt, or modern data tooling.
  • Experience running production experiments (A/B testing).
  • Experience mentoring junior colleagues and leading workstreams.

We care more about how you think, learn and apply your skills than about a specific number of years of experience.

Tech Stack:

  • Languages: Python, SQL
  • ML / Data: pandas, NumPy, scikit-learn, PyTorch, TensorFlow, NLP tooling
  • Backend: Django, Django REST Framework, GraphQL
  • Cloud & Ops: AWS, CI/CD, Datadog, CloudWatch
  • Data: Postgres, Databricks
  • Client: React, htmx (for context)
  • AI Tooling: ChatGPT, Claude, Gemini, Cursor

Ways of working:

  • Two-week sprints with planning and delivery tracked in Asana.
  • Daily stand-ups, async collaboration via Slack, and regular knowledge-sharing sessions.
  • Strong emphasis on autonomy, trust and a no-blame culture.
  • Regular collaboration with other ML and platform teams across Kraken.

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!

Senior Machine Learning Engineer - Utilities employer: Kraken Digital Asset Exchange

At Kraken, we are committed to fostering a dynamic and inclusive work environment where innovation thrives. As a Senior Machine Learning Engineer in our London office, you will be part of a passionate team dedicated to transforming the energy sector through cutting-edge technology, with opportunities for professional growth and collaboration across diverse teams. Enjoy a hybrid work model, a culture that prioritises autonomy and learning, 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 Senior Machine Learning Engineer - Utilities

✨Tip Number 1

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

✨Tip Number 2

Show off your skills! If you’ve got a portfolio of projects or contributions to open-source, make sure to highlight them. We love seeing practical applications of your machine learning expertise.

✨Tip Number 3

Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss how you’ve tackled real-world problems. We want to see your thought process and how you approach challenges.

✨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 Senior Machine Learning Engineer - Utilities

Machine Learning
Python
SQL
Data Analysis
Model Selection
Model Evaluation
Model Deployment
Monitoring
pandas
NumPy
scikit-learn
PyTorch
TensorFlow
Cloud Infrastructure (AWS)
MLOps

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 contribute to making a positive impact on the environment. Share any relevant projects or experiences that highlight your commitment to this cause.

Tailor Your Experience: Make sure to customise your application to reflect the specific skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your hands-on experience with ML in production environments and any relevant tools you've used. We love seeing how you fit into our vision!

Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your technical skills and experiences. Remember, we appreciate well-structured applications that make it easy for us to see your qualifications at a glance!

Apply Through Our Website: We encourage you to submit your application directly through our website. This helps us streamline the process and ensures your application gets the attention it deserves. Plus, it’s super easy to do!

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, model selection, and deployment. Be ready to discuss how you've applied these concepts in real-world scenarios, as this role requires a strong understanding of the full ML lifecycle.

✨Showcase Your Coding Skills

Prepare to demonstrate your Python and SQL skills during the interview. You might be asked to solve coding problems or explain your approach to writing maintainable and testable code, so practice coding challenges that reflect the complexity of production environments.

✨Understand the Tech Stack

Familiarise yourself with the tech stack mentioned in the job description, particularly libraries like pandas, NumPy, and frameworks like Django. Being able to discuss how you've used these tools in past projects will show your fit for the role.

✨Be Ready to Collaborate

This role involves working closely with product managers and engineers, so be prepared to discuss your experience in collaborative environments. Share examples of how you've contributed to team projects and tackled complex problems together.

Senior Machine Learning Engineer - Utilities
Kraken Digital Asset Exchange
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