Research Scientist (Supply Chain AI Startup)

An early-stage company builds a custom AI model for each client’s supply chain. Its small research group designs a single general architecture that pairs numerical modeling with LLM and reasoning systems, then tunes it to each client using their data. How quickly new clients can start depends mostly on how much research capacity exists.

Scope

Take an idea from hypothesis to a live production model and observe its effect in the physical world

Create models for forecasting and for optimization in settings with many interacting variables and shifting goals

Curate proprietary datasets that carry real signal about physical and commercial processes

Blend LLM knowledge with specialized numerical approaches for better precision and adaptability

Re-tune models as demand, new releases and global politics shift

Qualifications

Four or more years in industry on ML research, applied ML or LLM-based systems

Experience owning the full research cycle through to production deployment

A PhD in a quantitative field such as computer science, machine learning or statistics

Background in time series forecasting, mathematical modeling or optimization

Python and a deep learning framework (PyTorch or TensorFlow)

Preference for candidates whose experience goes beyond application-layer LLM work

On-site in the San Francisco Bay Area. Visa transfers are considered.