About Kraken
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—the company licences software to giants like Origin Energy in Australia and Tokyo Gas in Japan. We’re on a mission to accelerate the renewable transition, bringing 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 such as solar panels and heat pumps through software for engineers in the field. Our suite of AI tools pioneers ML and AI to make agents’ lives easier and customers happier. We do this by hiring clever, curious, and self‑driven people, giving them modern tools, infrastructure and autonomy.
Our ML team consists of ML, front‑end and back‑end engineers, enabling us to prototype quickly and bring innovative tools into production at breakneck speed.
What you’ll do
- 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 and the freedom to define novel approaches
- Help LLMs understand and interact with the millions of lines of code that run Kraken, leveraging GraphRAG, agentic workflows, finetuning, and reinforcement learning
- Use classic ML and NLP techniques to complement and improve LLM systems
- Act as a center of excellence for the whole business in AI, consulting other teams on LLM usage and lifting product quality across the organization
- Stay at the forefront of understanding AI advancements and their technical implications for the team and business
What you’ll need
- Curious and self‑driven – initiative to make decisions and find solutions to novel problems without excessive help
- 1+ year experience with production‑level LLMs beyond POC and deep technical understanding of diverse technologies and techniques to adapt LLMs to domains (advanced RAG techniques, tool calling, finetuning, RL); interest in AI software copilots or autonomous engineering bots
- 3+ years experience with traditional ML techniques, training and deploying non‑LLM models, and ongoing monitoring of production models incorporating feedback mechanisms to improve
- A keen interest in Gen AI and classic ML, understanding emerging trends and research, and proven experience aligning and applying this to real world objectives
It would be great if you had
- Experience working with large codebases and collaborating with multiple engineering teams in large companies
- Experience in diverse LLM deployment methods (hosted finetuned models via services like Bedrock, and running directly via engines like vLLM)
Culture & Perks
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.
We aim to create an inclusive environment. Please contact if you need accommodations or have preferences to customise the interview process.
Equal Opportunity Employer
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.
Applicant Notice
Our Applicant and Candidate Privacy Notice and Artificial Intelligence Notice, Website Privacy Notice and 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 GDPR and CCPA. If you would like more information about how your data is processed, please contact us.
Hiring Process
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.
