Machine Learning Engineer in Manchester
Machine Learning Engineer

Machine Learning Engineer in Manchester

Manchester Full-Time 36000 - 60000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Join a dynamic team to tackle cutting-edge AI challenges and innovate solutions.
  • Company: Kraken, a leader in renewable energy technology with a mission for a greener future.
  • Benefits: Enjoy competitive pay, flexible work options, and a supportive environment for growth.
  • Why this job: Make a real impact in the renewable energy sector while working with advanced AI technologies.
  • Qualifications: Experience with LLMs and traditional ML techniques; curiosity and self-drive are essential.
  • Other info: Be part of a certified Great Place to Work with excellent career development opportunities.

The predicted salary is between 36000 - 60000 £ per year.

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. We are on a mission to accelerate the renewable transition and bring affordable green energy to the world. We have 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 are 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. We have had great success in using AI to bring better service to customers, and we want to bring that success to the whole business. You will be part of a small expert team working on the most pressing problems for the business, whether it is internal AI tooling to make our developers twice as productive, or automating processes to cut months off migration times for new clients. You will 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.

You will have wide open problems to solve, so you will need to be comfortable with ambiguity, figuring out an approach and validating it fast. You will stay up to date with changes in the field, using your knowledge of state-of-the-art techniques to solve problems. LLMs will be your bread and butter, customised with advanced RAG techniques, finetuning and reinforcement learning. You will work closely with other engineers to build fast, and you will use Python and Kubernetes to deploy systems in production.

What you will 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 centre 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.

What you will need:

  • Curious and self-driven - in a field that changes so quickly, it is essential you have the initiative to make decisions yourself, and can find solutions to novel problems without lots of help and support.
  • 1+ year 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.
  • 3+ years experience of traditional ML techniques including training and deploying non-LLM 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 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 (e.g. hosted finetuned models via services like Bedrock, and running directly via engines like vLLM).

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. 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 and we will 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, we are 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.

Machine Learning Engineer in Manchester employer: Kraken

At Kraken, we pride ourselves on being a certified Great Place to Work, fostering a culture of innovation and collaboration that empowers our employees to thrive. As a Machine Learning Engineer, you'll join a dynamic team dedicated to pioneering AI solutions in the renewable energy sector, with ample opportunities for professional growth and development. Our commitment to autonomy, cutting-edge technology, and a supportive work environment makes Kraken an exceptional employer for those looking to make a meaningful impact in the world of green energy.
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Contact Detail:

Kraken Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer in Manchester

✨Tip Number 1

Network like a pro! Reach out to people in the industry, especially those at Kraken. A friendly chat can open doors that applications alone can't. Use LinkedIn or even our website to connect with current employees.

✨Tip Number 2

Show off your skills! If you’ve got a portfolio of projects or contributions to open-source, make sure to highlight them. We love seeing practical examples of your work, especially if they relate to ML and AI.

✨Tip Number 3

Prepare for the interview by brushing up on the latest trends in AI and ML. We’re looking for curious minds who can discuss cutting-edge techniques. Be ready to share your thoughts on how you’d tackle real-world problems at Kraken.

✨Tip Number 4

Don’t hesitate to apply even if you don’t meet every single requirement. We value diverse experiences and perspectives. If you think you’d be a good fit, go for it! Apply through our website and let’s see what magic we can create together.

We think you need these skills to ace Machine Learning Engineer in Manchester

Machine Learning
Large Language Models (LLMs)
Reinforcement Learning
Finetuning
Data Analysis
Natural Language Processing (NLP)
Python
Kubernetes
GraphRAG Techniques
Problem-Solving Skills
Collaboration
Adaptability
Curiosity
Technical Understanding of AI Systems

Some tips for your application 🫡

Show Your Curiosity: We love curious minds! Make sure to highlight your passion for learning and exploring new technologies in your application. Share examples of how you've tackled novel problems or kept up with the latest trends in AI and ML.

Tailor Your Application: Don’t just send a generic CV! Tailor your application to showcase your experience with LLMs and traditional ML techniques. Mention specific projects where you’ve used advanced RAG techniques or worked on AI software copilots to grab our attention.

Be Clear and Concise: When writing your application, clarity is key. Use straightforward language to explain your experiences and skills. We appreciate well-structured applications that get straight to the point without unnecessary fluff.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at Kraken!

How to prepare for a job interview at Kraken

✨Know Your Stuff

Make sure you brush up on the latest trends in machine learning and AI, especially around LLMs and techniques like RAG. Be ready to discuss how you've applied these in real-world scenarios, as Kraken is looking for someone who can hit the ground running.

✨Show Your Curiosity

Kraken values self-driven individuals, so come prepared with questions that show your interest in their mission and technology. Ask about their approach to renewable energy and how they see AI evolving in their operations.

✨Demonstrate Problem-Solving Skills

Be ready to tackle hypothetical problems during the interview. Think through your approach to ambiguous situations and explain how you would validate your ideas quickly. This will showcase your ability to adapt and innovate.

✨Collaborate and Communicate

Since you'll be working with various teams, highlight your experience in collaborating across departments. Share examples of how you've effectively communicated complex technical concepts to non-technical stakeholders, as this is crucial for success at Kraken.

Machine Learning Engineer in Manchester
Kraken
Location: Manchester

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