At a Glance
- Tasks: Build foundational AI capabilities and mentor teams on effective ML adoption.
- Company: Join Kraken, a leader in sustainable energy technology.
- Benefits: Enjoy a supportive work environment with great career growth and flexibility.
- Why this job: Make a real impact on the future of energy with cutting-edge AI technology.
- Qualifications: 3 years in ML engineering, strong Python skills, and cloud experience required.
- Other info: Be part of a certified Great Place to Work with a vibrant culture.
The predicted salary is between 48000 - 84000 £ 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.
You’ll work in the AI Foundations team which exists to enable AI across the entire company. We build the shared platforms, tooling and patterns that enable engineering & product teams to safely, reliably and efficiently use machine learning and generative AI across the business. This is not a research lab. This is a delivery-focused team that sits at the intersection of platform engineering, applied ML and developer enablement.
We’re looking for a Machine Learning Engineer to join our AI Foundations team. You’ll be building the core ML and AI capabilities that other teams rely on that make AI easy to adopt and hard to misuse. This role suits someone who enjoys thinking in systems, cares about engineering quality, and wants their work to multiply the impact of others.
What You’ll Do- This role differs from product‑embedded ML roles - your focus will be foundational capability, not a single feature or model.
- Build and maintain the foundational AI gateways and inference services used across Kraken to provide reliable and efficient access to ML and generative AI models.
- Architect and evolve internal evaluation tooling and monitoring frameworks that allow teams to measure the performance, quality, and safety of their systems at scale.
- Act as a technical mentor by teaching software engineers and ML specialists how to adopt foundational capabilities, ensuring AI is easy to use and integrated into everyday development.
- Create and maintain high‑quality documentation, internal guidance, and technical standards to help teams understand when and how to use AI effectively.
- Continuously improve Kraken's approach to AI enablement by balancing speed, cost, and quality within the infrastructure you manage.
- Work pragmatically - favouring solutions that work in production over theoretical perfection.
- 3 years of professional experience as a Machine Learning Engineer or similar applied ML role.
- Strong Python skills and experience with common ML libraries and frameworks.
- Practical experience taking ML models from development into production.
- Good understanding of software engineering fundamentals (version control, testing, CI/CD, etc.) and experience working with cloud infrastructure and data pipelines.
- An ability to explain ML concepts clearly to non‑ML engineers.
- A bias towards action, learning quickly, and improving systems over time.
- Prior experience building internal platforms or shared tooling.
- Exposure to MLOps practices, including model monitoring, evaluation, and deployment automation.
- Familiarity with considerations regarding data privacy, security, or responsible AI.
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 4.5 and in Germany we rate 4.7 on Kununu as a Top Company. Check out our Welcome to the Jungle site (FR/EN) to learn more about our teams and culture.
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’ll do what we can to customize your interview process for comfort and maximum magic!
As an equal opportunity employer, we do not discriminate on the basis of any protected attribute. We consider all applicants without regard to race, colour, religion, national origin, age, sex, gender identity or expression, sexual orientation, marital or veteran status, disability, or any other legally protected status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Senior Machine Learning Engineer - AI Foundations in London employer: Kraken Technologies Limited
Contact Detail:
Kraken Technologies Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer - AI Foundations in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Kraken. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Prepare a portfolio or a GitHub repo showcasing your machine learning projects. This is your chance to demonstrate your expertise and creativity beyond the CV.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by solving coding challenges and discussing ML concepts. The more you practice, the more confident you'll feel when it’s showtime.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, you’ll be part of our community from the get-go, which is always a bonus!
We think you need these skills to ace Senior Machine Learning Engineer - AI Foundations in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior Machine Learning Engineer role. Highlight your experience with ML libraries, cloud infrastructure, and any relevant projects that showcase your skills in building foundational AI capabilities.
Showcase Your Impact: When detailing your past experiences, focus on how your work has made a difference. Whether it’s improving systems or mentoring others, we want to see how you’ve multiplied the impact of your contributions in previous roles.
Be Clear and Concise: We appreciate clarity! Use straightforward language to explain your technical skills and experiences. Remember, you might be explaining complex ML concepts to non-ML engineers, so keep it simple and engaging.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for this exciting opportunity to join our AI Foundations team.
How to prepare for a job interview at Kraken Technologies Limited
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially those relevant to production environments. Be ready to discuss how you've taken models from development to production and the challenges you faced along the way.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common ML libraries and frameworks to ensure you're comfortable with them.
✨Understand the Bigger Picture
This role is about building foundational capabilities, not just individual features. Be prepared to discuss how your work can multiply the impact of others and how you approach system thinking in your projects.
✨Communicate Clearly
You’ll need to explain complex ML concepts to non-ML engineers. Practice simplifying your explanations and think of examples that illustrate your points clearly. This will show your ability to mentor and collaborate effectively.