Machine Learning Engineer

Kraken is the operating system for utilities of the future. Built in-house at Octopus Energy, we power energy companies and utilities around the globe with AI-powered tools 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. Kraken’s platform controls more than half of the grid-scale batteries in the UK. Our software helps engineers in the field adopt low carbon technologies like solar panels and heat pumps. Our platform enables our energy specialists to be the most productive in the industry, with AI tooling that makes agents more effective and customers happier. We hire clever, curious, and self-driven people, and provide modern tools, infrastructure, and autonomy.

Our ML team consists of ML, front-end and back-end engineers to rapidly prototype and deploy innovative tools.

You’ll join a small expert team working on the most pressing problems for the business, whether it’s internal AI tooling to boost developer productivity or automating processes to accelerate client migrations. You’ll work across the whole product lifecycle: identifying uses of new technologies through exploration, validating ideas with business teams, and rapidly prototyping. Your work will shape the pattern for AI success at the company.

You’ll have wide open problems to solve, so you’ll need to be comfortable with ambiguity and validating approaches quickly. You’ll stay up to date with field developments, applying state-of-the-art techniques to solve problems. LLMs will be your core focus, customized with advanced RAG techniques, fine-tuning and reinforcement learning. You’ll work with other engineers to build fast systems and deploy them in production using Python and Kubernetes.

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, with the freedom to define novel approaches
• Help LLMs understand and interact with Kraken's codebase, leveraging techniques such as GraphRAG, agentic workflows, fine-tuning, and reinforcement learning
• Apply classic ML and NLP techniques to complement and improve LLM systems
• Act as a center of excellence for AI across the business, consulting teams on LLM usage and elevating product quality
• Stay at the forefront of AI advancements and their technical implications for the team and business

What you'll need

• Curious and self-driven – ability to take initiative and solve novel problems
• 1+ year of production experience with LLMs beyond POC, with deep technical understanding of diverse technologies for domain adaptation (e.g., advanced RAG, tool calling, fine-tuning, RL)
• 3+ years of traditional ML experience, including training and deploying non-LLM models and monitoring production models that incorporate feedback
• Strong interest in Gen AI and classic ML, with demonstrated application to real-world objectives

It would be great if you had

• Experience working with large codebases and collaborating with multiple engineering teams
• Experience with diverse LLM deployment methods (e.g., hosted fine-tuned models via services like Bedrock, or engines like vLLM)

Equal opportunity and privacy

Kraken is a certified Great Place to Work in France, Germany, Spain, Japan and Australia. In the UK we are among the Best Workplaces on Glassdoor with a score of 4.7. Our Welcome to the Jungle pages (FR/EN) provide more about our teams and culture.

We are an equal opportunity employer and do not discriminate on the basis of race, color, 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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