Machine Learning Engineer

Machine Learning Engineer

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Kraken is the operating system for utilities of the future. Built in-house at Octopus Energy, we took them to become the biggest supplier in the UK, and now we power energy companies and utilities around the globe – in 10 countries and counting, licensing software to giants like Origin Energy in Australia and Tokyo Gas in Japan. We’re on a mission to accelerate the renewable transition, and bring affordable green energy to the world.

We’ve reinvented energy products with smart, data‑driven tariffs to balance customer demand with renewable generation, and Kraken’s platform controls more than half of the grid‑scale batteries in the UK. We’re driving the uptake of low‑carbon technologies like solar panels and heat pumps via our software for engineers in the field. Our platform allows our energy specialists to be the most productive in the industry, with our suite of AI tools making us pioneers in using ML and AI to make agents’ lives easier and customers happier.

We do it by hiring clever, curious, and self-driven people, enabling them with modern tools and infrastructure and giving them lots of autonomy.

Our ML team consists of ML, front‑end and back‑end engineers, so that we can rapidly prototype and get innovative tools in use at breakneck speed. We’ve had great success in using AI to bring better service to customers, and we want to bring that success to the whole business. You’ll be part of a small expert team working on the most pressing problems for the business, whether it’s internal AI tooling to make our developers twice as productive, or automating processes to cut months off migration times for new clients.

You’ll work across the whole product lifecycle: identifying uses of new technologies via exploration, working closely with teams around the business to validate that your ideas will bring value, and rapidly prototyping. The work you do will define the pattern for AI success at the company.

• Work with a high‑performance team of LLM, MLOps, backend and front‑end engineers
• Tackle the biggest problems facing the company, giving a wide experience across the business, with the freedom to define novel approaches
• Help LLMs understand and interact with the millions of lines of code that run Kraken, leveraging cutting‑edge techniques such as Graph
  
  RAG, agentic workflows, fine tuning, and reinforcement learning
• Use classic ML and NLP techniques to complement and improve LLM systems
• Act as a centre of excellence for the whole business in AI, consulting other teams on LLM use and lifting the quality of products across the organisation
• Be on the forefront of understanding AI advancements and their technical implications for the team and business

• Curious and self‑driven – in a field that changes so quickly, you must have the initiative to make decisions yourself and find solutions to novel problems without extensive help
• 1+ year experience with LLMs in production beyond POC and a deep technical understanding of diverse technologies and techniques to adapt LLMs to domains (e.g. advanced RAG techniques, tool calling, fine tuning and RL). Interest in cutting‑edge AI systems in software engineering, such as AI software copilots or autonomous engineering bots, is a particular plus
• 3+ years experience of traditional ML techniques, including training and deploying non‑LLM ML models, and ongoing monitoring of production models with feedback mechanisms to improve
• A keen interest in Gen‑AI and classic ML, understanding of emerging trends and research, and proven experience aligning and applying this to real‑world objectives

• Experience working with large codebases and collaborating with multiple engineering teams in large companies
• Experience in diverse LLM deployment methods (e.g. hosted finetuned models via services like Bedrock, and running directly via engines like vLLM)

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…