FPGA AI/ML Engineer (Part time)

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    "description": "<h2>Riverside Overview</h2>Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country’s most challenging technical problems.    All Riverside Research opportunities require U.S. Citizenship.  \n<h2>Position Overview</h2>\n<p>Riverside Research is seeking a part time Artificial Intelligence / Machine Learning Engineer with expertise in real-time processing and FPGA development. As a valued Riverside Research employee, you will be part of a highly skilled and integrated team that analyzes intelligence data and develops automation solutions to challenging Scientific & Technical problems.</p>\n<h2>Responsibilities</h2>\n<p><strong>FPGA experience</strong></p>\n<ul>\n <li>Design, implement, and optimize FPGA logic using AMD/Xilinx toolchains (Vivado, Vitis, HLS) development in VHDL/Verilog</li>\n <li>Integrate FPGA designs into larger systems, ensuring robust verification, documentation, and deployment across multiple platforms (Zynq, UltraScale+, Versal)</li>\n</ul>\n<p>        <strong>  AI/ML Algorithm R&D</strong></p>\n<ul>\n <li>Develop innovative machine learning and computer vision solutions to analyze and exploit large, complex datasets from remote sensing phenomenology</li>\n <li>Develop algorithms and associated software tools using C/C++/Python and associated machine learning libraries (PyTorch, LibTorch)</li>\n <li>Train AI/ML models and tune their hyperparameters for a given dataset and algorithm objectives</li>\n <li>Provide solutions for data collection and data linting that enable rapid, automated curation of training data</li>\n <li>Keep up with the SoTA practices for AI/ML</li>\n</ul>\n<p><strong>         Software development, documentation, and coding best practices:</strong></p>\n<ul>\n <li>Adhere to teams’ standards for reviewing source code, unit-testing, source code control, and documentation practicesUtilize Python PEP8 standards</li>\n</ul>\n<h2>Qualifications</h2>\n<p><strong><u>Required Qualifications:</u></strong></p>\n<ul>\n <li><strong>TS/SCI clearance.</strong></li>\n <li>Bachelors’ degree in either Computer Engineering, Electrical Engineering, Mathematics, Statistics, Physics, Computer Science, or related field of study</li>\n <li>Twelve years’ experience with FPGA development</li>\n <li>Seven years' experience with computer vision and/or AI/ML R&D algorithm development</li>\n <li>Experience with Git version control, branches, and merge conflict resolution</li>\n <li>Proficient in collaborative Office 365 tools such as MS Word, Excel, and PowerPoint</li>\n <li>Ability to work closely with subject-matter experts to develop tools, algorithms, and datasets needed for developing relevant and useful AI/ML prototype algorithms</li>\n <li>Self-driven, strong analytic, inferencing, critical thinking, and creative problem-solving skills</li>\n <li>Communicates highly technical results and methods clearly and succinctly</li>\n</ul>\n<p><strong><u>Desired Qualifications:</u></strong></p>\n<ul>\n <li>Advanced degree (MS/PhD) in Data Science, Mathematics, Statistics, Computer Science, a Physical Science or Engineering is strongly desired</li>\n <li>Experience with DoD intelligence production processes and workflows</li>\n <li>3+ years operational experience in radar signal processing analysis, overhead imagery analysis, orbital mechanics, and/or electronic warfare data analysis</li>\n <li>2+ years experience using data visualization tools and libraries in Python</li>\n <li>Experience with large (1 GB +) image data and formats such as HDF5, JSON, GEOTIFF, TFRecords, etc.</li>\n <li>Experience in development of distributed, web-based systems, service-oriented architectures, front-end user interfaces, and back-end databases are a plus</li>\n <li>Experience with interpretability of deep learning computer vision models including visualization and reasoning about model latent spaces and activation maps to assess model effectiveness / weaknessesFamiliarity in differences of supervised learning vs. unsupervised learning techniques</li>\n</ul>\n<h2>Global Comp</h2>$90.00 hr- $100/hr. This represents the typical compensation range for this position based on experience, location and other factors.\n<h2>Closing Statement</h2>  Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring.  Riverside offers comprehensive compensation and benefit packages to our employees. Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran’s status or any other status legally protected by applicable federal, state, and local law.",
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