AI Engineer

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CUBE is 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.

Role Overview

As a Machine Learning Engineer, you will drive the development and continuous improvement of our AI/ML‑powered products, including recommender systems, NLP solutions, and LLM‑driven features. Your mission is to deliver advanced, production‑ready ML solutions that delight users while maintaining excellence in cloud‑based ML engineering with equal focus on Development and Operations.

Key Responsibilities

• Develop, improve and productionise ML and LLM‑based features for our internal and external platforms to solve challenges such as high cardinality hierarchical classifications, personalised content filtering of legal documents, using ML/LLMs to network heterogeneous text data at scale, and building agent‑ready tools to leverage insights from our knowledge graph.
• Leverage cloud architecture (primarily Azure) to deploy interpretable ML/DL solutions that scale efficiently.
• Collaborate with SMEs to ground research proposals to CUBE’s dynamic, unstructured, high‑dimensional data.
• Continuously seek opportunities to innovate, learn, and apply the latest research to new products and services.

Requirements

Experience & Technical Skills

• At least two years of professional experience in ML, ideally within the NLP domain.
• Solid understanding of statistical and machine learning techniques with ability to select models that best suit the problem at hand.
• Ability to write clear, robust, and testable code in Python.
• Confident using SQL and NoSQL/graph databases.
• Solid understanding of data structures, data modelling, and software architecture, especially cloud‑based.

Mindset & Approach

• A systems thinking approach with ability to think in O(n) as much as plan product orchestration.
• An engineer who can keep up with mathematically and statistically‑oriented colleagues.
• Natural creativity with a track record of exploring innovative use cases of data and applications of statistical/ML methods.
• Strong communication skills, capable of explaining complex technical concepts to employees across the business.

Desirable

• Experience building and deploying LLM‑based agentic solutions into production.
• Solid understanding of recommender system principles and how they work.
• Demonstrated proficiency through GitHub profiles/online portfolios, Stack Overflow or Kaggle contributions.
• Experience or interest in neurosymbolic AI.
• A healthy sense of humour, or short of this, a high weekly rate of Machine Learning puns.

Interested?

If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.

CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.