Responsibilities
- Lead and develop a team of engineers specializing in computer vision, defining technical strategy and growth paths
- Design and oversee full-scale image analysis systems, spanning data acquisition via drones to machine learning inference and output delivery
- Develop robust, production-ready Python code for processing images, photogrammetry workflows, and deploying ML models
- Create and train machine learning models to detect plant counts, measure crop height, evaluate health, and identify diseases or weeds from aerial data
- Oversee AWS cloud environments that handle high-volume image processing tasks
- Integrate cutting-edge technologies such as large vision-language models and foundation models into analytical pipelines
- Work closely with research biologists, IT, and operations to convert scientific requirements into functional technical systems
- Present technical progress and strategic direction to stakeholders across organizational levels, including executives
Responsibilities
- Lead a team of computer vision engineers, setting technical direction and developing talent
- Architect and maintain end-to-end image analysis systems — from drone capture through ML inference to data output
- Write production-quality Python code for image processing, photogrammetry pipelines, and ML model deployment
- Design and train machine learning models for plant counting, height measurement, health assessment, and disease/weed detection from aerial imagery
- Manage AWS cloud infrastructure supporting large-scale image processing workloads
- Drive the integration of emerging technologies (large vision-language models, foundation models) into the assessment pipeline
- Collaborate cross-functionally with R&D biologists, IT, and operational teams to translate scientific needs into technical solutions
- Communicate the team's vision and results to stakeholders at all levels, including executive leadership
Team
Structure: Lead a team of computer vision engineers
