Machine Learning Engineer

Overview

Machine Learning Engineer to develop and deploy production-grade computer vision and ML solutions focused on leveraging imagery and sensor data for agricultural breeding programs.

What you'll do

• Design, develop, and deploy computer vision models extracting quantitative digital traits from multi-modal imagery and sensor data.
• Build and maintain scalable phenomics pipelines for processing field plots with preprocessing, trait extraction, quality control, and delivery.
• Collaborate with plant breeders, researchers, product managers, engineers, and data scientists to validate outputs and ensure relevance.
• Deliver cloud-based data pipelines and workflow orchestrators for ingesting, transforming, and delivering imagery-derived features.
• Productionalize research code into maintainable services and optimize systems for performance, scalability, and reliability.
• Architect and deploy mobile-first AI products for image capture and real-time identification/classification/trait measurement.

What you'll need

• 5+ years of experience in machine learning engineering and data science roles.
• 4+ years of applied computer vision experience.
• Strong deep learning expertise for computer vision (e.g., CNNs, vision transformers, segmentation/detection models).
• ML frameworks experience including PyTorch, TensorFlow, Keras, scikit-learn, and XGBoost.
• Ability to productionalize ML models with strong Python and SQL engineering practices.
• MLOps/CI-CD, containerization (Docker), and one or more cloud platforms (AWS, GCP, Azure).

Details

• Work location: Remote, NC, United States.
• Salary range: $107,800 to $200,200 annually.