We are a commodities research firm looking for a Principal Software Engineer to work alongside remote sensing scientists on satellite algorithms and time series machine learning pipelines.



We conduct research on agricultural commodities systems around the world to provide supply side production forecasts using satellite remote sensing and boots-on-the-ground research.

We are in-person in St Louis, Missouri, and spend our time reading the latest academic research papers and then building novel systems from our findings. We enjoy quiet work hours and very low email loads (and no Slack).

We need your help to scale our existing cloud-based suite of forecasting systems as we move beyond our core commodities into new markets. You will drive decisions on tech stack and engineering best practices as we build new prototypes to expand the coverage of our academic-oriented research shop.

Highlights of joining us:

• Deep Work-coded, research-first work culture.

• Small team with profit share opportunities.

• Opportunities for international research travel (with paid linguistics training).

What we need you for:

• Choosing the best tech stacks to operationalize new prototypes.

• Optimizing existing cloud-based satellite machine learning algorithms and infrastructure.

• Formalizing CI/CD workflows.

• Showing us what we’re missing in terms of the current industry best practices.

What we’re looking for:

• Strong background in software engineering, ops, or systems at scale (ideally 3+ years in big tech).

• Proficiency in at least C++ and Python.

• Extensive experience with cloud infrastructure.

• Bonuses (not required but you would fit in well):

o Experience with geospatial data, including satellite imagery and/or location data.

o Background in time series machine learning theory (no LLM engineers).

o Proficient in Spanish or French (or an interest in learning).

o Know how to drive a tractor.