Department Contact: Samantha Lish, 575-646-1726, slish@nmsu.edu
Internal or External Search: Internal - Open to Regular NMSU employees only (temporary/Term employees not eligible)
Advertising Summary: The Jornada Experimental range is looking for a R&D Software Developer, Spec position with a focus on projects aimed at advancing beef production and improving rangeland resilience across the Western United States.
Position Details
Position Title: R&D Software Developer, Spec
College/Division: Agricultural Experiment Station
Department: 317250-JORNADA EXPER RANGE HEADQUARTERS
Location: Las Cruces
Offsite Location (if applicable):
Target Hourly/Salary Rate: Commensurate with education and experience
Appointment Full-time Equivalency: 1.0
FLSA Status: Exempt
Bargaining Unit Announcement: This is NOT a bargaining unit position with American Federation of State, County & Municipal Employees (AFSCME).
Contingent Upon Funding: Contingent upon external funding
Standard Work Schedule: Standard (M-F, 8-5)
If Not a Standard Work Schedule:
Job Duties and Responsibilities: ***THIS POSITION IS A ONE YEAR APPOINTMENT, CONTINGENT UPON FUNDING***
The Jornada Experimental Range seeks applicants for an R&D Software Developer with strong expertise in software engineering and data science. The successful candidate will have demonstrated experience developing AI-driven data pipelines using advanced machine learning, deep learning, and Large Language Model (LLM) applications in agriculture. The candidate must demonstrate proficiency in Python and Java programming for backend applications, React for frontend development, and possess a foundational understanding of livestock production systems in arid U.S. rangelands. The successful applicant will contribute scientifically and technically to state and federally funded projects aimed at advancing beef production and improving rangeland resilience across the Western United States. This position involves close collaboration with interdisciplinary teams spanning animal and range science, electrical engineering, and computer science.
Lead development of a web-based platform to collect, curate, analyze, and visualize livestock, climate, and remote sensing data acquired through distributed IoT sensor networks in near real-time.
•Design and implement advanced computational intelligence and machine learning pipelines to analyze livestock behavior and vegetation dynamics using multimodal sensor data, including proximal and satellite remote sensing.
Develop and maintain scalable data server architectures and data services infrastructure.
•Interpret, organize, and coordinate scientific research addressing complex systems.
•Prepare analyses and documentation for peer-reviewed scientific publications and present findings at professional meetings.
•Develop competitive grant proposals to secure funding for research activities.
Qualifications
Required Education and Experience:
Associate's Degree + 11 years of relevant experience or a Bachelor's degree + 9 years of relevant experience. Master's degree or higher preferred.
Equivalent Qualifications:
Preferred Qualifications:
•Ph.D. in Computer Science, Data Science, Biosystems Engineering, or a closely related field.
•Strong publication record in peer-reviewed journals related to computer science, data mining, machine learning, artificial intelligence, and agricultural informatics.
•Minimum of five years of professional experience in software development and data science.
•Experience designing data architecture using relational and NoSQL databases.
•Experience developing web applications and mobile applications.
•Experience with cloud and edge computing infrastructures.
•Demonstrated ability to conduct independent research.
•Experience with machine and deep learning frameworks such as scikit-learn, TensorFlow, Keras, or PyTorch.
•Experience with LoRaWAN and IoT applications in precision agriculture.
•Knowledge of current issues and emerging directions in AI and machine learning.
•Proficiency in Java, JavaScript, and Python.
•Experience with Google Earth Engine (GEE) pipelines.
•Familiarity with web frameworks such as Flask, Django, Spring, and Bootstrap.
•Experience with web servers (e.g., Nginx, Apache) and application servers (e.g., Gunicorn, Unicorn, Express.js).
•Experience with cloud platforms such as AWS EC2, Microsoft Azure, or Google Cloud Platform.
Successful applicants should be highly motivated and creative. They should be willing to work independently and as a part of a diverse and multi-disciplinary team.
Special Certification/Licensure:
Working Conditions and Physical Effort
Environment: Work is normally performed in a typical interior/office work environment.
Physical Effort: No or very limited physical effort required.
Lifting Requirements: Requires handling of average-weight objects up to 10 pounds or some standing or walking.
Risk: No or very limited exposure to physical risk.