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- Tasks: Build core ML capabilities to drive AI adoption across departments.
- Company: Leading global technology firm in the energy sector.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Join a team making a real impact in sustainable energy through innovative AI solutions.
- Qualifications: 3 years of experience, strong Python skills, and MLOps familiarity.
- Other info: Work at the cutting edge of platform engineering and applied machine learning.
The predicted salary is between 43200 - 72000 £ per year.
A leading global technology firm in energy is looking for a Machine Learning Engineer to join their AI Foundations team. This role focuses on building core ML capabilities that enhance the adoption of AI across departments.
Ideal candidates will have around 3 years of experience, strong Python skills, and familiarity with MLOps. The position offers an opportunity to work at the intersection of platform engineering and applied machine learning, contributing to impactful projects in sustainable energy.
Senior ML Engineer - AI Foundations: Build Core AI Gateways in London employer: Kraken Digital Asset Exchange
Contact Detail:
Kraken Digital Asset Exchange Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer - AI Foundations: Build Core AI Gateways in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at the company you're eyeing. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those that align with sustainable energy. This will help us see your practical experience and passion for the field.
✨Tip Number 3
Prepare for the technical interview! Brush up on Python and MLOps concepts, and be ready to discuss how you've applied them in real-world scenarios. We love seeing candidates who can think on their feet!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always on the lookout for talent that fits our vision for AI in energy.
We think you need these skills to ace Senior ML Engineer - AI Foundations: Build Core AI Gateways in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your strong Python skills in your application. We want to see how you've used Python in your previous projects, especially in relation to machine learning and MLOps.
Demonstrate Your Experience: With around 3 years of experience being ideal, don’t shy away from detailing your past roles. We’re keen to know how you’ve contributed to ML projects and what impact they had on your team or company.
Connect with Our Mission: Since we’re focused on sustainable energy, it’s a great idea to mention any relevant projects or interests you have in this area. Show us how your work aligns with our goals and values!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to shine in front of our hiring team!
How to prepare for a job interview at Kraken Digital Asset Exchange
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially those relevant to the energy sector. Be prepared to discuss algorithms, model evaluation, and how you've applied these in past projects. This will show your depth of knowledge and passion for the field.
✨Showcase Your Python Skills
Since strong Python skills are a must, be ready to demonstrate your coding abilities. You might be asked to solve a problem on the spot or discuss your previous projects. Practise coding challenges and be familiar with libraries like TensorFlow or PyTorch.
✨Understand MLOps Practices
Familiarity with MLOps is crucial for this role. Prepare to discuss how you’ve implemented MLOps in your previous work, including deployment strategies and monitoring models in production. This will highlight your ability to bridge the gap between development and operations.
✨Connect Your Work to Sustainable Energy
Since the company focuses on sustainable energy, think about how your experience aligns with their mission. Be ready to share examples of how your work in machine learning can contribute to sustainability efforts, showcasing your commitment to impactful projects.
