Senior Engineer, Human Machine Teaming (R5649)

Job description

Job responsibilities

• Design and run HMT experiments that instantiate baseline and context-sensitive collaborative work requirements profiles and test whether these hold under varied conditions.
• Conduct robustness and resilience testing, perturbing, for instance, communications, sensor data, autonomy behavior, workload, and time pressure to find the limits of teaming.
• Characterize the context sensitivity of requirements profiles across environments, platforms, and operator populations.
• Extend operator-in-the-loop (OITL) and live-virtual-constructive (LVC) testing with HMT-specific experimentation.
• Define HMT-specific quantitative and qualitative measures of performance, effectiveness, and success, build assessment batteries for operator situation awareness, workload, decision making, calibration, reliance, and…
• Translate findings into prioritized recommendations, revisions to requirements profiles, and feature requests for Development Leads, and co-create a shared HMT body of knowledge.
• Contribute evidence to the HMT maturity scale, risk assessment, and the Hivemind assurance case, and report results to engineering and customer audiences.
• Travel to company, test, demonstration, and customer locations to conduct project work (approximately 25%).

Job requirements

• Engineer II: typically requires a minimum of 2 years of related experience with a Bachelor's degree; or 0 years and a Master's degree; or a PhD without experience.
• A degree in human factors engineering or psychology, cognitive systems engineering, applied cognitive science, industrial and systems engineering, or a related field.
• Working knowledge of human machine teaming, human factors, and human performance theory and measurement, including cognitive task analysis and knowledge elicitation.
• Sound grasp of quasi-/experimental design, between- and within-participant designs, and control of extraneous confounds, experience conducting human participants research, proficiency with multivariate statistical…
• Experience in multidisciplinary settings, and ability to work in complex, ambiguous problem spaces and produce clear and structured artifacts.
• Strong teamwork and collaboration skills, and written and verbal communication skills.
• Hands-on experience with human machine teaming, MUM-T, human-robot interaction, or applied artificial intelligence, specifically in mission autonomy applications such as UAV Groups 1–5.
• Experience with developmental or operational test and evaluation, including OITL and LVC testing.