Agronomic Modeler (Corn)

Location: Davis, CA, USA

Salary: $125,000–$175,000 per year plus benefits

Company

InnerPlant develops living plant sensors and the CropVoice platform to detect crop stress early and help farmers optimize in-season decisions.

What you will do

• Build and maintain statistical and mechanistic models for corn diseases and insect pressure, including tar spot, gray leaf spot, southern rust, and lepidopteran pests.
• Create and evaluate statistical and machine learning models for corn disease risk and spray timing.
• Validate model performance against field observations from a Midwest research network and plant-based sensor data.
• Connect model outputs with fluorescence detections, weather data, and corn phenology to generate field- and zone-level recommendations.
• Collaborate on data-input and model-output pipelines.
• Explain model results and technical concepts clearly to agronomists, growers, and other non-engineers.

Requirements

• Bachelor’s or Master’s degree in a STEM field; a PhD is preferred.
• At least 3 years of experience building and deploying relevant models.
• Experience with ecological or biophysical modeling, including statistical modeling, machine learning, and geostatistics.
• Knowledge of corn agronomy and corn disease modeling, including disease susceptibility, residue and rotation effects, canopy microclimate, and fungicide application windows.
• Proficiency in Python and the Python scientific stack.
• Experience with version control, package managers, CI/CD pipelines, and cloud infrastructure.

Culture & Benefits

• Work on agricultural sensing technology designed to improve yields and reduce input costs.
• Collaborative and transparent working style with a focus on continuous model improvement.
• Insurance benefits.
• Flexible time off.
• Opportunity to contribute to the design of future agricultural systems.