MTS - Research Scientist
- Location
- San Francisco
- Workplace
- On-site
- Compensation
- $200k – $300k + equity
About this role
Omnifold designs a purpose-built model for each customer's supply chain. The research team owns the core of that: a generalized model architecture combining quantitative modeling with language and reasoning models, then fine-tuned per customer on their own data. The team is three people today with a fourth joining shortly, and research capacity is what gates how fast new customers come on.
You will feel at home here if you want to run your own research end to end and see it hit a production system inside weeks.
What You'll Do.
Own the research cycle. Take a hypothesis through to a production model, with direct visibility into the physical outcome it changes.
Design forecasting and optimization models. Work across multi-variable environments where the objectives shift as business conditions do.
Build proprietary data assets. Curate data that carries signal about real physical and commercial systems.
Fold in LLM reasoning. Combine language model knowledge with purpose-built quantitative models to lift accuracy and adaptability.
Keep models current. Retune as consumer sentiment, product launches, and geopolitical conditions move.
What happens next
Skip the application pile. I get you in front of the people who decide.
Confirm the fit
A few questions to make sure this role is the right shape for you. Two minutes.
I pitch you to the company
I write the intro, send it to the founder, and handle the back-and-forth.
A meeting lands on your calendar
When the company wants to meet, I get the call on your calendar. You just show up.
Culture & values
Team consists of AI PhDs, professors, and technologists from MIT, Stanford, Google, Palantir, and Snowflake
Engineers are hands-on builders who think clearly and add value beyond delegation
Early-stage energy with Series B funding but Series A startup team size and impact per person
Team moves quickly and ships with confidence
Everyone is expected to be hands-on and contribute directly
Works together 5 days a week at San Francisco HQ fostering tight collaboration and rapid decision-making
Team embraces AI tools for development while maintaining strong engineering fundamentals
Intentionally small and exceptionally high-caliber team of 17 people
Plans to grow thoughtfully as the company scales
Know someone who'd be great for this?
