Senior Machine Learning Engineer

The Senior Machine Learning Research Engineer researches and applies cutting-edge techniques for extracting information from an ever-growing data environment that is increasingly fundamental for new and emerging National Security capabilities being developed, tested, and deployed by the Department of Defense, the Intelligence Community, and other National Security organizations. As a Two Six Technologies (TST) Machine Learning (ML) Research Engineer, your primary area of focus will be adversarial ML research within the computer vision and/or audio domains. You will provide subject matter expertise and mentoring to ML researchers on multiple teams, creating products based on state-of-the-art industry and academic concepts. You will create, analyze, and red-team ML systems, ensuring their functionality and robustness in a variety of situations. 

Duties

• Develop novel adversarial ML attacks to evaluate the robustness of innovative ML algorithms and defenses from leading publishers in academia and industry
• Synthesize results and research from evaluation findings to advance the state-of-the-art and guide future research for ML adversarial methods
• Adapt these results from the virtual to the physical domain
• Partner with engineers to build and maintain a leading adversarial ML testbed currently used by several industry, government, and academic partners
• Evaluate the viability of ML solutions for multiple programs, focusing on adversarial ML research within the computer vision and/or audio ML domains
• Work collaboratively with peers, including software developers and research scientists, in an agile environment on a fully-remote team
• Communicate your methods and results to a variety of stakeholders and customers

Requirements

• 2+ years experience in ML or related fields
• Technical degree in CS, EE, math, or similar field, or equivalent experience
• Experience developing in Python and in using PyTorch, TensorFlow, or JAX
• Experience with common machine learning pipelines, model architectures, and metrics
• Experience reading and analyzing academic publications in machine learning

Nice-to-haves

• Academic or industry conference publications in relevant disciplines
• Experience with agile development, CI testing, MLOps, code reviews, and developing as part of a larger team
• Familiarity with Department of Defense ML use cases and operational requirements
• An active security clearance

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