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. Were on a mission to accelerate the renewable transition and bring affordable green energy to the world.
Weve reinvented energy products with smart data driven tariffs to balance customer demand with renewable generation and Krakens platform controls more than half of the grid-scale batteries in the UK. Were 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.
Weve had great success in using AI to bring better service to customers and we want to bring that success to the whole business. Youll be part of a small expert team working on the most pressing problems for the business whether its internal AI tooling to make our developers twice as productive or automating processes to cut months off migration times for new clients. Youll 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.
Youll have wide open problems to solve so youll need to be comfortable with ambiguity figuring out an approach and validating it fast. Youll stay up to date with changes in the field using your knowledge of state-of-the-art techniques to solve problems define the research direction and shape the product. LLMs will be your bread and butter customized with advanced RAG techniques finetuning and reinforcement learning. Youll work closely with other engineers to build fast and youll use Python and Kubernetes to deploy systems in production.
What youll 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 with the freedom to define novel approaches
Work to help LLMs understand and interact with the millions of lines of code that run Kraken leveraging techniques at the cutting-edge of the technology like 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 as a floating resource that consults other teams use of LLMs and lifts the quality of products around the whole business
Be on the forefront of understanding AI advancements and their technical implications for the team and business
Work with technical and product leadership in the team to develop research avenues and priorities to solve problems
Mentor and inspire other MLOps and ML engineers on the team to support their technical development
What youll need
Curious and self driven - in a field that changes so quickly its essential you have the initiative to make decisions yourself and can find solutions to novel problems without lots of help and support
2 years experience with LLMs in production beyond POC and a deep technical understanding of diverse technologies and techniques to adapt LLMs to domains (like advanced RAG techniques tool calling finetuning and RL)
Of particular interest are cutting-edge AI systems in software engineering for example working on AI software copilots or autonomous software engineering bots
5 years experience of traditional ML techniques including training and deploying ML models and ongoing monitoring of production models that incorporate 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 business 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 (eg hosted finetuned models via services like Bedrock and running directly via engines like vLLM)
Experience as a thought leader of engineering excellence internally and externally including conference or meetup talks
Kraken is a certified Great Place to Work in France Germany Spain Japan and 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 and well 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 were 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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