AI Engineer driving development of ML and LLM-based features for CUBE's regulatory compliance SaaS solutions. Collaborating with experts to innovate and apply advanced AI technologies in a hybrid environment.
Responsibilities
Drive the development and continuous improvement of AI/ML-powered products.
Develop, improve and productionise ML and LLM-based features.
Leverage cloud architecture primarily Azure to deploy interpretable ML/DL solutions.
Collaborate with SMEs for research proposals targeting CUBE’s dynamic data.
Continuously seek opportunities to innovate, learn, and apply the latest research to new products and services.
Requirements
At least two years of professional experience in ML, ideally within the NLP domain.
Solid understanding of statistical and machine learning techniques.
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.
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.
Experience building and deploying LLM-based agentic solutions into production is desirable.
Solid understanding of recommender system principles is also desirable.
Demonstrated proficiency through GitHub profiles, Stack Overflow or Kaggle contributions is desired.
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