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- Tasks: Design and build ML-powered products that transform the energy sector.
- Company: Leading tech company in the UK with a focus on innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Make a real impact by shaping solutions that drive the future of energy.
- Qualifications: Strong ML fundamentals and software engineering experience required.
- Other info: Collaborative team environment with exciting challenges ahead.
The predicted salary is between 43200 - 72000 £ per year.
A leading technology company in the United Kingdom is seeking a Senior Machine Learning Engineer to design, build, and scale ML-powered products. This hands-on, product-focused role requires strong ML fundamentals and experience in software engineering within a collaborative team environment.
The ideal candidate will contribute to the technical direction and best practices while addressing real customer use cases. Join us in shaping innovative solutions that impact the energy sector and beyond.
Senior ML Engineer – AI-Driven Energy Utilities in London employer: Kraken
Contact Detail:
Kraken Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer – AI-Driven Energy Utilities in London
✨Tip Number 1
Network like a pro! Reach out to folks in the energy and tech sectors on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those relevant to energy utilities. This gives us a taste of what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on your ML fundamentals and software engineering principles. We want to see how you think and solve problems, so practice explaining your thought process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior ML Engineer – AI-Driven Energy Utilities in London
Some tips for your application 🫡
Showcase Your ML Skills: Make sure to highlight your machine learning expertise in your application. We want to see how you've designed and built ML-powered products in the past, so don’t hold back on those details!
Emphasise Collaboration: Since this role is all about teamwork, let us know about your experiences working in collaborative environments. Share examples of how you’ve contributed to a team’s success and tackled challenges together.
Tailor Your Application: Take the time to customise your application for this specific role. We’re looking for someone who understands the energy sector and can address real customer use cases, so make sure to connect your experience to our needs.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity with us!
How to prepare for a job interview at Kraken
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals before the interview. Be prepared to discuss algorithms, model evaluation metrics, and how you’ve applied these in real-world scenarios. This will show that you have a solid foundation and can contribute effectively to the team.
✨Showcase Your Software Engineering Skills
Since this role requires strong software engineering experience, be ready to talk about your coding practices and any projects you've worked on. Bring examples of your work, especially those that demonstrate your ability to design and scale ML-powered products.
✨Understand the Energy Sector
Familiarise yourself with current trends and challenges in the energy sector. Being able to discuss how machine learning can address specific use cases in energy utilities will set you apart and show your genuine interest in the field.
✨Prepare for Collaborative Scenarios
This role is all about teamwork, so think of examples where you’ve successfully collaborated with others. Be ready to discuss how you handle feedback, share knowledge, and contribute to a positive team environment. This will highlight your fit within their collaborative culture.
