About this role
The Head of Research at Omnifold is a full-time leadership position based in San Francisco, suiting an experienced artificial intelligence professional ready to scale a research team. The role centers on guiding the development of frontier models designed for forecasting, prediction, optimization, and control.
Role Overview
Omnifold seeks a leader for its research team in San Francisco to train frontier models targeting supply chain use cases. The team consists of professors and PhD alumni from institutions like OpenAI, Adept, Google, Stanford, and MIT. The primary objective for this position is to scale the research organization from five to twenty individuals while building systems that surpass current state-of-the-art algorithms.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
About the Company
Omnifold trains frontier models for forecasting and optimization with a focus on supply chain applications. The company addresses physical consequences resulting from inaccurate forecasting, such as unnecessary manufacturing, storage, emergency air freight, and poor production planning. The corporate mission focuses on eliminating waste and accelerating growth for companies dealing with physical products.
How to Apply
Interested candidates should apply directly on the official Omnifold careers page.
Skills and tech stack
Questions candidates ask
Where is the Head of Research position located?
The role is located at the Omnifold headquarters in San Francisco and requires working in-person five days per week.
What is the primary focus of the research at Omnifold?
Research focuses on training frontier models for forecasting, prediction, optimization, and control, specifically targeting supply chain use cases.
What management background is required for this role?
Candidates must have at least first-line or second-line management experience, as the remit involves scaling a team from five to twenty researchers.
What educational background is needed?
A background in machine learning foundations is required, specifically a PhD in computer science theory, statistics, econometrics, operations research, systems engineering, mathematics, or theoretical physics.