Job Description

About the Department
The Precision Sustainable Agriculture program is a network of researchers across the country collaborating to develop integrated knowledge-intensive sustainable agriculture practices into a precision framework to maximize farm productivity and sustainability through the use of an information ecology that connects farms, data, tools, and people for optimal, real-time decision making. The PSA program is housed within the Department of Crop and Soil Sciences which encompasses diverse disciplines in research extension and teaching. The department’s mission is to develop future leaders in crop, soil and environmental sciences, improve crop plants and products, devise effective and sustainable crop production systems, devise effective and sustainable soil management techniques in both agriculture and urban settings; and disseminate crop, soil, and environmental science knowledge for the benefit of users and producers of food, feed turf, biofuels and fiber in North Carolina, the nation and the world.
Essential Job Duties
This position will design, develop, and deploy computer vision based machine learning models that solve complex business problems for agriculture applications. The position will work closely with our team to implement and deploy machine learning solutions for edge devices.

Responsibilities will include, but are not limited to:
Designing and implementing machine learning models using deep learning techniques
Developing and maintaining computer vision models for various tasks within the agricultural domain
Deploying machine learning models on the edge for real-time inference
Evaluating and comparing data acquisition strategies and sensor modalities for automation in agriculture
Optimizing model efficiency for inference on resource-constrained devices
Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions
Other duties as assigned
Other Responsibilities
Qualifications
Minimum Education and Experience
A Master’s Degree and 1-2 years of experience or a Bachelor’s Degree with 2-4 years of experience or an equivalent combination of education, training, and relevent experience.
Experience with real-world applications or deployment of computer vision tasks on real world data.
Experience with computer vision tasks such as object detection, segmentation, or instance segmentation.
Other Required Qualifications
Knowledge of deployment of machine learning models on edge devices.
Knowledge of optimizing models for inference, including experience with techniques such as model pruning, quantization, and distillation.
Excellent communication skills and ability to work effectively in a team environment.
Preferred Qualifications
Strong experience with deep learning frameworks such as TensorFlow or PyTorch.
Required License(s) or Certification(s)
Valid Driver’s License and the ability to obtain an NC Driver’s License within 60 days of hire.

The position will be required to drive a program vehicle to various sites where public transportation will not be avaliable.