Human-Machine Teaming Test & Evaluation Lead

MORSE is seeking an Human-Machine Teaming Test & Evaluation (T&E) Lead to work with our customers in the DC/VA area for some of our highest-profile Artificial Intelligence and Machine Learning programs. This role will split time onsite with customers and MORSE locations. You will also be working with our customers to shape the future of machine learning in the DOD.

RESPONSIBILITIES

• Define goals and expectations for Human-Machine Teaming T&E performance for artificial intelligence applications

• Research best practices and new techniques for artificial intelligence operational T&E, human-AI teaming, and how to measure the operational efficiency of AI with users

• Lead strategy and coordination with military users and analysts, vendors, and customers

• Lead testing exercises and demonstrations with end users, elicit feedback, and define metrics to determine successful human-AI performance

• Find ways to convert Human-Machine Teaming T&E findings into Systems T&E and Algorithm T&E tests

• Working with government team, co-contractor teams, data team, model development team, user feedback

SKILLS AND REQUIREMENTS

Candidates that have the ability to interface with external military customers will excel. The ideal candidate will have a proven record of successful defense program management with a deep knowledge of human factors or operational performance. Technically strong individuals will thrive in this role.

• US Citizenship with Top Secret clearance and SCI eligibility is required

• MS or PhD in human factors, human systems engineering or related field (preferred)

• 5+ years of experience, and at least 5 of these years in program management in aerospace and defense or related domain

• Expertise in human computer interaction (HCI), human-machine teaming (HMT), human-AI teaming, or operational test and evaluation (OT&E)

• Experience working with intelligence analysts and military users

• Experience coordinating and performing operational assessments of technology with end users

• Ability to lead a multi-disciplinary team

• Ability to communicate to stakeholders, vendors, and internal teams

• Travel requirements: 10-25%

• Understanding of artificial intelligence and machine learning disciplines (statistics, data science, big data, deep learning, computer vision) is a plus