• Typically requires a bachelors, masters degree or PhD in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and progressive machine learning engineering experience as follows; five or more years of experience with a bachelors degree or three or more years of experience with a masters degree. May substitute equivalent machine learning engineer experience in lieu of education. • Must have an advanced understanding of machine learning concepts, principles, and theory. Experience building neural network architectures, constructing training and evaluation pipelines, debugging and improving model behavior, developing metrics, continuous model learning and improvement. • Applied experience in one or more of the following areas: reinforcement learning, imitation learning, large language models, world models, robotics, autonomous systems, control systems • Experience with Python, C++, Docker, Pytorch, Tensorflow, Gym, Pettingzoo, AFSIM, SQL • Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance. • Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment. • Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience. • Must be able to work both independently and on a team. • Must have a demonstrated history of applying novel technical solutions in fast evolving product areas. • Able to work extended hours as required. • Ability to obtain and maintain a DoD security clearance is required