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Omnifold

Head of Research

Posted Yesterday
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In-Office
San Francisco, CA, USA
Entry level
In-Office
San Francisco, CA, USA
Entry level
Lead and scale a research team from 5 to 20 researchers developing frontier machine learning systems for forecasting, optimization, and control. The role requires strong ML foundations, hands-on experience training and deploying production models, and first- or second-line management experience. Preferred qualifications include LLM infrastructure expertise, quantitative modeling experience, and startup experience. This is an in-person role in San Francisco, five days per week.
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Head of Research

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:

Must have

  • 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)

Nice to have

  • Experience with LLM infrastructure - inference, fine-tuning, RL etc.

  • Success in environments with quantitive models (quant research fund, ranking, ads)

  • Startup experience

Location:

  • San Francisco (in-person, 5 days per week)

Omnifold’s Mission

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 eliminate waste and accelerate growth for every company with physical products.

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