Computer Programmer (Remote)

For over 25 years, National Experienced Workforce Solutions (NEW Solutions) has specialized in connecting experienced workers (ages 55+) with full-time and part-time job opportunities that support the critical missions of Federal Agencies across the United States.

NEW Solutions connects experienced workers (ages 55+) with the USDA Agricultural Research Service (ARS). These experienced professionals provide administrative, scientific, and technical support to the Agricultural Research Service through the Experienced Worker Program (EWP).

Positions listed here do not guarantee employment for any definite period. Enrollment in the Experienced Worker Programs administered by NEW Solutions is temporary. The enrollment relationship between NEW Solutions and the Enrollee is an ?at-will? relationship. This means that an Enrollee is free to terminate enrollment at any time during the enrollment period, and NEW Solutions and the Agency have the right to terminate the relationship with the Enrollee.

PLEASE NOTE: An ?Enrollee? is not a federal employee, nor an employee of NEW Solutions. An ?Enrollee? is a participant in a grant program established through a Cooperative Agreement funded by the agency and administered by NEW Solutions. The enrollee shall not sign federal documents, authorize the use of federal funds, nor initiate or conduct federally funded research projects. The enrollee shall not author articles for publication as a federal employee, nor coordinate scientific research between the Government and private industry. The enrollee shall not present themselves as a Government employee or Government representative at meetings both foreign and domestic or when coordinating federal agencies? areas of research. The enrollee shall not make decisions on federally based research on behalf of Government policy makers, and the enrollee shall not supervise any Government employees.

This opportunity applies to applicants legally eligible to work in the United States.

*This position will be open until filled. NOTE: This position has the option to work remotely.

Minimum of 3 year(s) of experience in software development, embedded systems, robotics, or sensor integration. OR BA/BS Degree in Science, Software Engineering, Data Science, Robotics, Electrical/Computer Engineering, or related field.

• Strong Python experience required; C++ experience strongly preferred.
• Experience with sensor integration, embedded systems, or robotics (Raspberry Pi, microcontrollers) is beneficial.
• Familiarity with numerical methods (NumPy, SciPy), point-cloud libraries (Open3D, PCL), and data-synchronization techniques.
• Ability to write clean, maintainable, well-documented code.
• Experience with LiDAR or IMU data is a plus but not required.
• Ability to work independently with minimal supervision.
• Experience required with Windows, MS Word, MS Excel
• Python, Git, CMake, Open3D, NumPy/SciPy, sensor-fusion libraries, Raspberry Pi toolchains.

This position will support python coding work to develop precision agricultural tools and the data processing pipelines for data generated by the new precision agricultural tools. These tools will make U.S. dairy farms more profitable and productive. The enrollee shall not sign federal documents, authorize the use of federal funds, nor initiate or conduct federally funded research projects. The enrollee shall not author articles for publication as a federal employee, nor coordinate scientific research between the Government and private industry. The enrollee shall not present themselves as a Government employee or Government representative at meetings both foreign and domestic or when coordinating federal agencies? areas of research. The enrollee shall not make decisions on federally based research on behalf of Government policy makers, and the enrollee shall not supervise any Government employees.

• Refactor, maintain, and document existing Python and C++ codebase for a LiDAR data-collection and processing system. Assist with code curation, version management, documentation, and reproducibility improvements for long-term research use. 70%
• Improve backend data-fusion algorithms, including timestamp alignment, IMU orientation corrections, encoder-based spatial registration, and LiDAR point-cloud construction. 10%
• Develop or refine analytical modules (e.g., canopy height, LAI estimation, stand count/topology methods, voxelization, beam penetration, per-plot summaries). 10%
• Implement a user-friendly processing interface (config header or lightweight GUI) enabling non-technical users to load scans and produce standardized outputs. 10%

• Physical requirements: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of this position.