Senior Machine Learning Engineer - AI Foundry at Kraken

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

03 May, 26

Salary

0.0

Posted On

02 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, Data Science, LLM, Production Deployment, Collaboration, Evaluation Practices, Experimentation, Monitoring, Iteration, Backend Engineering, Client Delivery, Data Analysis, Ambiguity Management, AWS, Docker, Kubernetes

Industry

technology;Information and Internet

Description

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 join our AI Foundry team — a small, expert group focused on solving high-impact problems for the business by building production-grade internal AI tooling. We're looking for a Senior Machine Learning Engineer where your work will span the full lifecycle: exploring solutions, validating value with stakeholders, rapidly prototyping, and taking systems to production (and keeping them healthy). You’ll work closely with product, backend engineers, and operational stakeholders to deliver tools that directly improve how we serve clients and run Kraken. Example initiatives you may contribute to include: - An LLM-powered assistant for internal knowledge and discovery - Summarising code changes to support client delivery and decision-making - Helping teams assess and accelerate client migrations \n What You'll Do Build and ship LLM-powered internal tools that improve knowledge access, reduce time spent on discovery, and support client delivery outcomes Take ownership of projects end-to-end: problem framing → experimentation → engineering → production deployment → monitoring and iteration Design and operate LLM systems in the real world (quality, latency, cost, reliability), including strong evaluation practices and fast feedback loops Use classic ML / data science skills to complement LLM approaches where appropriate (e.g., ranking, classification, analytics, measurement) Work hands-on in a Python-first ecosystem to build services, pipelines, and tooling that are maintainable, testable, and production-ready Collaborate closely with backend engineers, product, and internal users (including Client Delivery Leads) to define MVPs, iterate quickly, and drive adoption Contribute to a culture of strong engineering practices, pragmatic experimentation, and continuous learning What We're Looking For Proven experience using LLMs in production (beyond a proof of concept) - you can clearly explain what shipped, what users needed, and how you managed trade-offs Strong end-to-end delivery experience: you’ve taken ML/LLM work into production and owned it beyond launch Solid data science and analysis skills: you’re comfortable working with large datasets, defining metrics, evaluating system performance, and diagnosing failures High proficiency in Python (this is the core language across our data and ML stack) Comfort operating in ambiguity: you can move from a fuzzy problem to a clear plan, validate assumptions quickly, and iterate It Would Be Great If You Had Experience with AWS, and deploying/operating systems using Docker and/or Kubernetes Familiarity with the Python data/ML ecosystem (e.g., Pandas, PyTorch) Experience building internal tooling used by operational teams, and driving adoption through iteration and feedback Exposure to large codebases and cross-team collaboration in product-led engineering environments \n 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 at inclusion@kraken.tech 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 Kraken, 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. 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. U.S. based candidates can learn more about their EEO rights here. Our (i) Applicant and Candidate Privacy Notice and Artificial Intelligence (AI) Notice, (ii) Website Privacy Notice and (iii) Cookie Notice govern the collection and use of your personal data in connection with your application and use of our website. These policies explain how we handle your data and outline your rights under applicable laws, including, but not limited to, the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Depending on your location, you may have the right to access, correct, or delete your information, object to processing, or withdraw consent. By applying, you acknowledge that you’ve read, understood and consent to these terms

Responsibilities

You will build and ship LLM-powered internal tools that improve knowledge access and support client delivery outcomes. Additionally, you will take ownership of projects from problem framing to production deployment and monitoring.