Applied Scientist - Machine Learning and AI for Structured Data

Applied Scientist 3

You will be responsible for designing new approaches for fine tuning tabular foundation models and inference on tabular foundation models (including those with graph transformer architectures) with structured data, creating agentic systems for multi-faceted data analysis, developing advanced personalization and customization techniques, and integrating your solutions into intelligent applications for industry verticals. You will conduct in-depth research, produce production-ready scalable code, and collaborate with a cross-functional team to integrate your work into applications and services. You will be responsible for designing automated data quality assessment, automated data transformation for non-normal distributions and data asset search. 

This role requires deep expertise in transformer models, machine learning, data science and generative AI, including large tabular foundation models (fine-tuning, adaptation, personalization), agents/agent frameworks, and tool orchestration. Preferred qualifications include practical experience with machine learning approaches for structured data, tabular representation learning, graph transformers, graph neural networks, time series modeling, and operations research/mathematical optimization.

Candidates should have the demonstrated ability to design novel solutions that advance the state of the art in response to business requirements, as evidenced by publications in first-tier conferences or journals and impact on successfully deployed software products that operate at scale.