AI Systems Engineer

3 weeks ago

England, United Kingdom CUBE Full time

Role: AI Systems Engineer

Location: UK (Remote-first)


Recently listed as a "RegTech Top Performer" in Market Fintech's RegTech Supplier Performance Report, CUBE is pioneering the development of machine automated compliance.


We are a global RegTech business defining and implementing the gold standard of regulatory intelligence and change for the financial services industry. We deliver our services through a SaaS platform, powered by an innovative combination of AI and proprietary data ontology, to simplify the complex and everchanging world of compliance for our clients.


At CUBE, we are creating the future and are a company rooted in strong values, team spirit and commitment to our customers and wider communities. We serve some of the largest financial institutions globally and are expanding our footprint very fast. As we do so, we are keen for new talent to join us and realize their full potential to grow into leadership positions within the business.


Our Products:

RegPlatform is a technology platform that streamlines regulatory change management. It provides firms with a one-stop, continuously maintained inventory of global regulations, with effortless horizon scanning, integration capabilities and workflow management. RegPlatform combines industry leading AI technology with expert validated insights to simplify the complexities of multi-jurisdictional regulatory content.

RegBrain allows customers to apply CUBE's AI models directly to their own content, enabling faster release and feedback cycles. Our flagship AI services will be included, spanning structural detection, classification, entity extraction, summarisation, and recommendations. Available to customers and partners as APIs and via a UI.


Role mission:

The mission of the AI System Engineer is to ensure that the ML driven systems RegBrain deploys are fit for purpose and sound at the time of deployment and during their whole life. The role has touch-points throughout the life-cycle of a model, from conception to maintenance, including research and requires advances knowledge of NLP.


Responsibilities:

  • Participate in the defining and scoping of research projects so as to allow maximum innovation.
  • Advocate for solutions and designs that leverage prior or expert knowledge, whether it be for classical or generative ML systems.
  • Understand who the operators of the AI systems will be and design for their operational needs (e.g. explainability, usability, adaptability to casual and power users)
  • Review data availability and work with Data Engineers to ensure that systems are in place to track the quality of signals over time, and identify the sub-systems impacted by change.
  • Participate in research projects to ensure that the solutions explored fit within the wider ecosystem and that a holistic enquiry on model performance is demonstrated in research reports/papers.
  • Ensure that AI system testing and performance evaluation is sound, systematic and addresses needs of engineers and stakeholders.
  • Until Operations becomes a separate unit, ensure the visibility of the health state of in-production systems to C-level.


What we’re looking for:

  • A M shaped individual that strives for expertise in Data Engineering, Operations and Machine Learning from a system point of view.
  • An AI enthusiast that understands that a game-changer solution is one made of good design, good data, good modeling and good orchestration.
  • An ambitious coder that can draft baseline solutions across the whole lifecycle of an AI driven product with support from Data engineers, Operations engineers, Cloud engineers, Machine Learning engineers, infrastructure engineers and front-end engineers.
  • A growth minded individual with a good mix of creative thinking and scientific rigour.


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