Careers · Calgary, Canada

Help wanted

Steady work. Unsolved problems. Fresh air.

Join a frontier research team building the digital brain for the world's food production.

Three young applicants read a notice board on the porch of a prairie general store. One carries a portable computing machine in an open case, one holds a finned tube module, and one wears headphones and holds a rolled diagram.

The work

Your model will go to work in a real field.

Research here ships. We train foundation models, compress them onto edge hardware, and bolt them to machines that feed people.

  • 01

    Hard problems

    Reasoning that abstains, vision at the edge, autonomy that is safe around people and crops.

  • 02

    Real stakes

    Every point of accuracy shows up in a farmer's season and in what goes on the land.

  • 03

    Open research

    We publish datasets, models, and tools on GitHub and Hugging Face.

The classifieds

Who we look for.

Research scientists

Foundation models for agriculture. Reasoning, self-supervised learning, multimodal perception, and evaluation. You will work on Beyond and SEED.

Edge and systems engineers

Model acceleration on NVIDIA Orin AGX and Thor AGX. Real-time pipelines, vector compression, and orthomosaics stitched in motion.

Agent engineers

Maya's voice, telephony, messaging, and meeting skills, and the integrations that let her work inside a farm's existing software.

Robotics and autonomy engineers

Autopilot for aerial and ground vehicles, precision sprayer control, and the SOLV survey computer.

Agronomists

Ground truth for everything we build. Weed science, crop nutrition, herbicide resistance, and field trials.

Field and customer teams

The people who put Maya to work on real farms and bring back what the lab needs to hear.

Open roles

Now hiring.

Open roles will be posted here.

Until then, send a note and a résumé to info@precision.ai and tell us what you want to build.

Before you apply

Read the work first

Read what we have published, then tell us where we are wrong.