At a Glance
- Tasks: Join a high-performance team tackling innovative AI and ML challenges.
- Company: Kraken, a leader in renewable energy technology with a global impact.
- Benefits: Great workplace culture, competitive salary, and opportunities for professional growth.
- Why this job: Make a real difference in the renewable energy transition with cutting-edge technology.
- Qualifications: 1+ year experience with LLMs and 3+ years in traditional ML techniques.
- Other info: Inclusive environment with a focus on collaboration and innovation.
The predicted salary is between 36000 - 60000 ÂŁ per year.
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 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.
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.
Machine Learning Engineer in City of London employer: Kraken
Contact Detail:
Kraken Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in City of London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Kraken or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and ML techniques. This is your chance to demonstrate your expertise and passion for AI and machine learning.
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you've tackled challenges in past projects and how you can contribute to Kraken's mission.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the Kraken team.
We think you need these skills to ace Machine Learning Engineer in City of London
Some tips for your application 🫡
Show Your Curiosity: We love curious minds! Make sure to highlight your initiative and problem-solving skills in your application. Share examples of how you've tackled challenges or explored new technologies in your previous roles.
Tailor Your Experience: When applying, focus on your experience with LLMs and traditional ML techniques. We want to see how your background aligns with our mission at Kraken, so don’t hesitate to showcase relevant projects or achievements.
Be Authentic: Let your personality shine through in your written application. We value authenticity and want to get a sense of who you are beyond your technical skills. Don’t be afraid to share your passion for AI and renewable energy!
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. This helps us keep track of your application and ensures it reaches the right people in our team. We can’t wait to hear from you!
How to prepare for a job interview at Kraken
✨Know Your ML Stuff
Make sure you brush up on your machine learning knowledge, especially around LLMs and traditional ML techniques. Be ready to discuss your experience with production-level models and how you've tackled real-world problems using these technologies.
✨Show Your Curiosity
Kraken values self-driven individuals who are curious about AI advancements. Prepare examples of how you've taken the initiative in past projects or how you've kept up with emerging trends in AI and ML. This will show that you're not just knowledgeable but also passionate about the field.
✨Collaborate Like a Pro
Since you'll be working with various engineering teams, highlight your experience in collaborating on large codebases. Share specific instances where teamwork led to successful outcomes, and be ready to discuss how you can contribute to Kraken's collaborative culture.
✨Ask Smart Questions
Prepare thoughtful questions about Kraken's approach to AI and ML, especially regarding their innovative tools and practices. This not only shows your interest in the role but also gives you insight into how you can fit into their mission of accelerating the renewable transition.