AI/ML Engineer (Part Time)

Riverside Research Institute•Fairborn, OH

1d•$20 - $35

About The Position

Riverside Research is seeking a part-time Artificial Intelligence / Machine Learning Engineer to support existing contracts to prototype and develop automation solutions to NASIC’s most difficult Scientific & Technical Intelligence problems. As a highly valued and sought-after Riverside Research employee, you will be part of a highly skilled and integrated team that analyzes intelligence data to discover opportunities for automated solutions.

Requirements

Ability to obtain TS/SCI clearance
Bachelor’s Degree in either Electrical Engineering, Mathematics, Statistics, Physics, Computer Science, or related field of study
Experience with AI/ML, software R&D, or related experience
Proficiency in Python-based AI/ML model development
Awareness of version control, branches, merge conflict resolution, and git in general
Proficient in collaborative Office 365 tools such as MS Word, Excel, and PowerPoint
Ability to work closely with subject-matter experts to develop tools, algorithms, and datasets needed for developing relevant and useful AI/ML prototype algorithms
Self-driven, strong analytic, inferencing, critical thinking, and creative problem-solving skills
Communicates highly technical results and methods clearly and succinctly

Nice To Haves

Pursuing advanced degree (MS/PhD) in Data Science, Mathematics, Statistics, Computer Science, a Physical Science or Engineering is strongly desired
1+ years' experience with AI/ML, software R&D, or related experience
Experience with DoD intelligence production processes and workflows
Experience in radar signal processing analysis, overhead imagery analysis, orbital mechanics, and/or electronic warfare data analysis
Experience using data visualization tools and libraries in Python
Visualizations/Web Development Skills (e.g., Tableau, MEAN stack - MongoDB, ExpressJS, AngularJS, NodeJS)
Experience with large (1 GB +) image data and formats such as HDF5, JSON, GEOTIFF, TFRecords, etc.
Experience in development of distributed, web-based systems, service-oriented architectures, front-end user interfaces, and back-end databases are a plus
Experience with interpretability of deep learning computer vision models including visualization and reasoning about model latent spaces and activation maps to assess model effectiveness / weaknesses
Familiarity in differences of supervised learning vs. unsupervised learning techniques

Responsibilities

AI/ML Algorithm R&D
Develop innovative machine learning and computer vision solutions to analyze and exploit large, complex datasets from remote sensing phenomenology
Develop algorithms and associated software tools using Python and associated machine learning libraries (PyTorch, TensorFlow)
Train AI/ML models and tune their hyperparameters for a given dataset and algorithm objectives
Provide solutions for data collection and data linting that enable rapid, automated curation of training data
Keep up with the SoTA practices for AI/ML
Software development, documentation, and coding best practices: Adhere to teams’ standards for reviewing source code, unit-testing, source code control, and documentation practices
Utilize Python PEP8 standards
FPGA experience
Design, implement, and optimize FPGA logic using AMD/Xilinx toolchains (Vivado, Vitis, HLS) development in VHDL/Verilog
Integrate FPGA designs into larger systems, ensuring robust verification, documentation, and deployment across multiple platforms (Zynq/Zynq UltraScale+, Versal, or custom boards)