Senior AI​/ML Engineer

Riverside Overview

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.

Riverside Research is seeking an 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.

AI/ML algorithm development for prototype applications in remote sensing:

• Develop prototype AI/ML algorithms and associated software tools using Python and the Python/Tensor Flow API
• Train AI/ML models and tune their hyperparameters for a given dataset and algorithm objectives
• Visualize hyperparameter optimization spaces with Tensorboard for selection of optimal parameters for a given parametric (functional) Tensor Flow model

AI/ML dataset generation, curation, and management:

• Provide customized solutions to data quality control that ensure accurate functional mappings for AI/ML algorithms on complex remote sensing datasets
• Develop databases / data lakes / data warehouses for organizing both structured and unstructured datasets

AI/ML algorithm R&D:

• Apply machine learning and general computer vision best practices and methods to analyze and exploit large, complex remote sensing datasets from a variety of remote sensing phenomenology
• Keep up with the SoTA practices for AI/ML, perform relevant R&D, and implement new and innovative ideas in machine learning and high-performance computing to solve long-standing remote sensing “big-data” exploitation problems

Software development, documentation, and coding best practices:

• Contribute and adhere to the AI team’s standards for reviewing and unit-testing code, lead or participate in team-wide code reviews, and adhere to standardized documentation practices
• Utilize Python PEP8 standards

• Must have minimum of Secret with able to obtain and maintain a TS/SCI clearance.
• 8 years and a Bachelor’s Degree in either Electrical Engineering, Mathematics, Statistics, Physics, Computer Science, or related field of study
• Must demonstrate proficiency in Python-based end-to-end AI/ML model development lifecycle using a recent deep learning platform (Tensor Flow preferred)
• Awareness of version control, branches, merge conflict resolution, and git in general
• Proficient in collaborative Office 365 tools such as MS Word, Excel, and Power Point
• 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

• Advanced degree (MS/PhD) in Data Science, Mathematics, Statistics, Computer Science, a Physical Science or Engineering with 10 years of experience is strongly desired
• Active TS/SCI Security Clearance
• Experience with DoD intelligence production processes and workflows
• 3+ years operational experience in radar signal processing analysis, overhead imagery analysis, orbital mechanics, and/or electronic warfare data analysis
• 2+ years 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

$120,000- $185,000 This represents the typical compensation range for this position based on experience, location and other factors.