The AI planning platform purpose-built for your business. Discover the growth, margin, and cash your generic planning tools can. Backed by Kleiner Perkins and Lightspeed.
About the role
Every bad forecast has a physical consequence. Unnecessary goods are manufactured, shipped, and stored. Emergency air freight is needed for misallocated products. Poor production planning means workers show up with nothing to do, or work frantic overtime. Inefficiency is everywhere.
What they're looking for
- Background in ML foundations (i.e. PhD in CS theory, statistics, econometrics, operations research / systems engineering, math, or theoretical physics)
- Hands on experience training and deploying production ML models
- First-line or second line management experience minimum (remit is to scale a team from 5-20 researchers)
More about this role
Omnifold trains frontier models for forecasting and optimization. Our research team is professors and PhDs from OpenAI, Adept, Google, Stanford, and MIT. We build systems to outperform the state of the art algorithms in prediction, optimization, and control, with a focus on supply chain use cases. We are looking for a leader with the following background:
Background in ML foundations (i.e. PhD in CS theory, statistics, econometrics, operations research / systems engineering, math, or theoretical physics)
Hands on experience training and deploying production ML models
First-line or second line management experience minimum (remit is to scale a team from 5-20 researchers)
Experience with LLM infrastructure - inference, fine-tuning, RL etc.
Success in environments with quantitive models (quant research fund, ranking, ads)
Startup experience
San Francisco (in-person, 5 days per week)
Every bad forecast has a physical consequence. Unnecessary goods are manufactured, shipped, and stored. Emergency air freight is needed for misallocated products. Poor production planning means workers show up with nothing to do, or work frantic overtime. Inefficiency is everywhere.
Our mission is to...
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