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Fundamental is an AI company pioneering the future of enterprise decision-making. Founded by DeepMind alumni, Fundamental has developed NEXUS – the world's most powerful Large Tabular Model (LTM) – purpose-built for the structured records that actually drive enterprise decisions. Backed by world class investors and trusted by Fortune 100 companies, Fundamental unlocks trillions of dollars of value by giving businesses the Power to Predict. At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI.
Job Responsibility
Helping to identify, characterize and evaluate data sources, including realistic synthetic data generated from Structured Causal Models and physical / systems-based simulators
Building and maintaining ETL pipelines
Designing and implementing scalable, reliable data storage solutions
Collaborating with the rest of the research team to maintain a reliable, efficient training pipeline where data is a critical component
Collaborating with the wider engineering and infrastructure team
Requirements
Experience with: Identifying good data sources to train and evaluate ML models, including real-world and realistic synthetic data sources
Bringing data from structured and unstructured sources, as well as simulators and causal models, into formats accessible by ML models