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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 hours, 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 in a team setting.
- Other info: Collaborative environment with exciting challenges and career advancement.
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 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
✨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 that extra step to connect with us directly.
We think you need these skills to ace Senior ML Engineer – AI-Driven Energy Utilities
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your machine learning fundamentals and software engineering experience in your application. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this specific role. Mention how your past experiences can contribute to our mission of shaping innovative solutions in the energy sector.
Be Yourself: We’re looking for someone who fits into our collaborative team environment. Let your personality shine through in your application – we want to know what makes you tick!
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. It’s the easiest way for us to review your application and get you on board!
How to prepare for a job interview at Kraken
✨Know Your ML Fundamentals
Brush up on your machine learning concepts and algorithms. Be ready to discuss how you've applied these in real-world scenarios, especially in energy utilities. This shows you not only understand the theory but can also implement it effectively.
✨Showcase Your Software Engineering Skills
Prepare to talk about your experience with software engineering practices. Highlight any projects where you’ve built or scaled ML products. Discuss your coding style, version control, and how you ensure code quality in a collaborative environment.
✨Understand the Energy Sector
Familiarise yourself with current trends and challenges in the energy sector. Be prepared to discuss how your skills can address specific customer use cases. This demonstrates your interest in the field and your ability to contribute meaningfully.
✨Emphasise Collaboration
Since this role is team-focused, be ready to share examples of how you've worked effectively in teams. Discuss your approach to collaboration, problem-solving, and how you handle feedback. This will show that you’re a great fit for their culture.
