At a Glance
- Tasks: Design and build AI-powered systems to tackle real-world energy challenges.
- Company: Join a leading tech company revolutionising the energy sector for a sustainable future.
- Benefits: Enjoy competitive pay, flexible working, and opportunities for personal growth.
- Why this job: Make a meaningful impact on global energy solutions while advancing your career.
- Qualifications: Experience in machine learning and software engineering is essential.
- Other info: Be part of a dynamic team with a strong culture of collaboration and innovation.
The predicted salary is between 48000 - 84000 £ 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). We’re in a very exciting growth phase, and have 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
- Help 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!
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.
Senior Machine Learning Engineer - Utilities employer: Kraken
Contact Detail:
Kraken 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 Kraken employees on LinkedIn. 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 technical interviews by brushing up on your ML fundamentals and coding skills. Practice explaining your thought process clearly; we want to see how you tackle problems, not just the final answer.
✨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
Some tips for your application 🫡
Show Your Passion for Sustainability: When writing your application, let your enthusiasm for creating a sustainable future shine through. We want to see how your skills in machine learning can contribute to making a positive impact in the energy sector.
Tailor Your Experience: Make sure to highlight your hands-on experience with machine learning and software engineering. We’re looking for specific examples of how you’ve tackled complex problems and delivered real-world solutions, so don’t hold back!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to explain your technical skills and experiences, as we want to understand your thought process without getting lost in jargon.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to join our growing team at Kraken Utilities!
How to prepare for a job interview at Kraken
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially around data analysis, model selection, and deployment. Be ready to discuss how you've applied these concepts in real-world scenarios, as this will show your depth of understanding and practical experience.
✨Showcase Your Coding Skills
Since the role requires strong Python skills, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot or explain your approach to writing maintainable code. Practise coding challenges beforehand to boost your confidence!
✨Understand the Business Impact
Familiarise yourself with how machine learning can solve real business problems, particularly in the utilities sector. Be prepared to discuss specific examples of how your work has improved customer experiences or operational efficiency in previous roles.
✨Collaborate and Communicate
This role involves working closely with product managers and engineers, so highlight your collaboration skills. Think of examples where you’ve successfully communicated complex technical concepts to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between tech and business.