Machine Learning Engineer
Kraken
- City of London, England, United Kingdom
- City of London, England, United Kingdom
About
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 inclusion@kraken.tech 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.
#J-18808-Ljbffr
Languages
- English
Notice for Users
This job comes from a TieTalent partner platform. Click "Apply Now" to submit your application directly on their site.