Machine Learning Performance Engineer

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CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients. CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the worlds top financial institutions globally.
Our make it happen culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.
With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success.
We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.
As ML Engineer, RegBrain, your mission is to:
Develop advanced NLP and AI-based products that will delight users.
Provide excellence in cloud-based ML engineering, with as much focus on Operations as Development.
As a machine learning engineer, your main responsibility is to conduct the development andproductionisationof ML and NLP-based features for CUBEs products - a SaaS Platform (RegPlatform) and an API (RegConnect).
Develop optimal ML & NLP solutions for RegBrain use cases, from baseline to SOTA approaches, wherever appropriate.
Produce high quality, modular code, and deploy following our established DevOps CI/CD and best practices.
Improve the efficiency, performance, and scalability of ML & NLP models (this includes data quality, ingestion, loading, cleaning, and processing).
Stay up-to-date with ML & NLP research, and experiment withnew models and techniques.
Engage with them to raise standards of Software engineering.
Propose cloud architectures for ML-based products that need new infrastructure.
Participate in the monitoring and continuous improvement of existing ML systems.
But what is more important than raw number of years of experience isdemonstrated proficiency(through GitHub profiles/online portfolios and the interview process itself). Bonus points for Stack Overflow and Kaggle contributions!
Experience analyzing large volumes of textual data (almost all of our use cases will involve NLP).
Ability to write clear, robust, and testable code, especially in Python.
Familiarity with SQL and NoSQL/graph databases.
Extensive experience with ML & DLplatforms,frameworks, and libraries.
Solid understanding of data structures,data modelling, and software architecture, especially cloud-based.
If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. We celebrate diversity and are committed to creating an inclusive environment for all employees.
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Location:
London
Job Type:
FullTime

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