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- Tasks: Join us to solve exciting problems in energy using cutting-edge machine learning techniques.
- Company: Kraken is revolutionizing the energy sector with innovative, AI-driven solutions for a sustainable future.
- Benefits: Enjoy a supportive environment, flexible work options, and opportunities for personal growth.
- Why this job: Make a real impact on the energy transition while working with passionate, like-minded individuals.
- Qualifications: Passion for energy, experience with LLMs, and a strong engineering mindset are essential.
- Other info: We encourage all candidates to apply, regardless of meeting 100% of the qualifications.
The predicted salary is between 30000 - 42000 £ per year.
Help us use technology to make a big green dent in the universe!
Kraken powers some of the most innovative global developments in energy.
We’re a technology company focused on creating a smart, sustainable energy system. From optimising renewable generation, creating a more intelligent grid and enabling utilities to provide excellent customer experiences, our operating system for energy is transforming the industry around the world in a way that benefits everyone.
It’s a really exciting time in energy. Help us make a real impact on shaping a better, more sustainable future.
Kraken Customer
What we do: build the most AI-driven, innovative, forward-thinking platform for energy management. From optimising resources to delivering cost-effective, exceptional customer experiences through advanced Customer Information Systems (CIS), billing, meter data management, CRM, and AI-driven communications, Kraken is powering the next wave of innovation in the energy industry.
Why we do it: future energy will not look like energy as we know it today. We need to not just think about our future, but build for it. Now.
You’ll have wide open problems to solve, so you’ll need to be comfortable with ambiguity, figuring out an approach and validating it fast. You’ll stay up to date with changes in the field, using your knowledge of state-of-the-art techniques to solve problems and defining the research direction and shape the product. LLMs will be your bread and butter, customized with advanced RAG techniques or finetuned where appropriate. You’ll work closely with other engineers to build fast, and you’ll use Python and Kubernetes to deploy systems in production.
What You’ll Need
- Passion about working in energy and contributing to the energy transition
- Curiosity and a self driven approach – 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
- Ability to learn quickly and enthusiasm about learning new technologies
- Strong experience with LLMs in production, and techniques to customize models to the domain like RAG or finetuning
- A solid base experience of traditional ML techniques including training and deploying non-LLM ML models
- An engineering mindset – passion for building robust tools
- Experience with some of the following technologies: Python, Using LLMs in production, ML python packages like pytorch, huggingface and scikit-learn, NLP, Kubernetes, SQL to prepare datasets for training and performance tracking
It would be great if you had
- Experience of building a cutting-edge AI systems beyond PoC, for example internal tooling for developers that has a proven impact on productivity
- Experience in diverse LLM deployment methods
- Experience working with large codebases and collaborating with multiple engineering teams in large companies
If this sounds like you then we’d love to hear from you.
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. Need any specific accommodations? Whether you require specific accommodations or have a unique preference, let us know, and we’ll 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 Octopus, we’re 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. Our commitment is to provide equal opportunities, an inclusive work environment, and fairness for everyone.
Seniority level
- Entry level
Employment type
- Full-time
Job function
- Engineering and Information Technology
Industries
- Technology, Information and Internet
Referrals increase your chances of interviewing at Kraken by 2x
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Machine Learning Engineer employer: Kraken
Contact Detail:
Kraken Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarize yourself with the latest advancements in LLMs and RAG techniques. Being able to discuss these topics confidently during your interview will show your passion and knowledge in the field.
✨Tip Number 2
Demonstrate your engineering mindset by preparing examples of robust tools or systems you've built in the past. Highlight how these projects have made a tangible impact, especially in collaborative environments.
✨Tip Number 3
Stay updated on the energy sector's trends and challenges. Showing that you understand the industry's direction and how your skills can contribute to its evolution will set you apart from other candidates.
✨Tip Number 4
Network with professionals in the energy tech space, especially those working with AI and machine learning. Engaging in discussions or attending relevant meetups can provide insights and connections that may benefit your application.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Company: Dive deep into Kraken's mission and values. Familiarize yourself with their innovative approach to energy management and how they leverage technology to create a sustainable future.
Highlight Relevant Experience: Make sure to emphasize your experience with LLMs, Python, and any relevant ML techniques. Showcase specific projects or achievements that demonstrate your ability to solve complex problems in the energy sector.
Show Your Passion: Express your enthusiasm for working in the energy field and your commitment to contributing to the energy transition. Personal anecdotes or motivations can help convey your genuine interest.
Tailor Your Application: Customize your CV and cover letter to align with the job description. Use keywords from the posting, such as 'Kubernetes', 'RAG techniques', and 'AI-driven communications' to ensure your application stands out.
How to prepare for a job interview at Kraken
✨Show Your Passion for Energy
Make sure to express your enthusiasm for working in the energy sector. Talk about why you are passionate about contributing to the energy transition and how you see technology playing a role in shaping a sustainable future.
✨Demonstrate Your Curiosity
Highlight your self-driven approach and curiosity. Be prepared to discuss how you stay updated with the latest developments in machine learning and energy technologies, and share examples of how you've tackled novel problems independently.
✨Discuss Your Experience with LLMs
Since LLMs are crucial for this role, be ready to talk about your hands-on experience with them. Discuss specific projects where you've implemented LLMs in production, including any techniques like RAG or finetuning that you've used.
✨Emphasize Collaboration Skills
Collaboration is key in this role, so be sure to mention your experience working with diverse engineering teams. Share examples of how you've contributed to large codebases and how you communicate effectively with team members to achieve common goals.
