Role & Responsibilities:
By contributing to the core of our AI research effort, you will be responsible for:
- Algorithms: Contribute to the development of foundation models for structured data.
- Evaluation: Continuously evaluate and optimize the performance of our models by building adapted metrics reflecting the use-cases of our clients, building upon the insights from our industrial and academic partners.
- Active learning and training data optimisation: Participate in the active learning strategy and implementation process to improve sample selection and future model performance. As well as designing and consolidating training and evaluation datasets to optimise representational as well as transfer learning abilities of our Tabular Foundation models.
- Research: Stay current with the latest ML advancements in the field and suggest optimisations that may improve the foundation models' performance and capabilities.
- Pitching & communication: present both ML research concepts to the scientific community and experimental design needs to the ML team.
- Collaboration: Work closely with ML engineers, data scientists, and clients to deliver promising representation algorithms for downstream applications.
- Ad-hoc analyses: Running analyses to understand the learning mechanisms of the foundation model.
