Descripción de la oferta
About Fundamental
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.
Key responsibilities
The greatest research is done through solid engineering. As part of the research team, you will contribute to development of breakthrough machine learning models by working on one of the most crucial aspects of ML model training: data. The main responsibilities of this role are:
Helping to identify, characterize and evaluate data sources
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
Must have
Experience with:
Identifying good data sources to train and evaluate ML models
Bringing data from structured and unstructured sources into formats accessible by ML models
Strong fundamentals of software engineering
Strong knowledge of:
Python
Python data processing stack (numpy, pandas, …)
Familiarity with:
distributed processing (e.g. Ray, Dask Spark, Beam)
data storage solutions
Basic ML knowledge
Nice to have
Contributions to open source ML projects
BSc/MSc/PhD in computer science/machine learning
Experience working with tabular data / predictive analytics
Experience working with "classical machine learning and deep learning" (pre-LLM)
Benefits
Competitive compensation with salary and equity
Comprehensive health coverage, including medical, dental, vision, and 401K
Fertility support, as well as paid parental leave for all new parents, inclusive of adoptive and surrogate journeys
Relocation support for employees moving to join the team in one of our office locations
A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action
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