Machine Learning Engineer, Kraken.tech

• 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
• 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

Desirable

• 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
• 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
• 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