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
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 systemsHelp 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 experienceDeep 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 TensorFlowComfort 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. 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. U.S. based candidates can learn more about their EEO rights here.
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.
