Machine Learning Engineer - Utilities at kraken123

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 [Upgrade to PRO to see contact] 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. 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