Senior Engineer, Human Machine Teaming
Conducts applied human-machine teaming experimentation for autonomous systems, testing collaboration robustness, operator performance, and failure limits. Requires a relevant degree, human participants research experience, experimental and multivariate analysis skills, and eligibility for U.S. DoD security clearances.
About the job
Responsibilities
- Design and run human-machine teaming (HMT) experiments under varied conditions.
- Conduct robustness and resilience testing across communications, sensor data, autonomy behavior, workload, and time pressure.
- Characterize requirements across environments, platforms, and operator populations.
- Extend operator-in-the-loop (OITL) and live-virtual-constructive (LVC) testing with HMT experimentation.
- Define quantitative and qualitative measures of performance, effectiveness, and success.
- Build assessment batteries for situation awareness, workload, decision-making, calibration, reliance, and trust.
- Prepare research protocols and analyze human-machine system data.
- Translate findings into recommendations, requirements revisions, and feature requests.
- Contribute to HMT maturity, risk assessment, and the Hivemind assurance case.
- Report results to engineering and customer audiences.
- Travel to company, test, demonstration, and customer locations approximately 25% of the time.
Requirements
- Engineer II: typically 2+ years of related experience with a bachelor's degree, or qualifying master's/PhD experience paths. Senior Engineer: typically 3–5 years of related experience with a bachelor's degree, or qualifying master's/PhD experience paths.
- Degree in human factors engineering, psychology, cognitive systems engineering, applied cognitive science, industrial and systems engineering, or a related field.
- Working knowledge of human-machine teaming, human factors, human performance theory and measurement, cognitive task analysis, and knowledge elicitation.
- Knowledge of quasi-experimental and experimental design, between- and within-participant designs, and control of extraneous confounds.
- Experience conducting human participants research.
- Proficiency with multivariate statistical analyses and tools such as SPSS, R, or Python.
- Ability to translate research results into design recommendations.
- Ability to work in multidisciplinary, complex, and ambiguous environments and produce clear, structured artifacts.
- Strong teamwork, collaboration, written communication, and verbal communication skills.
- U.S. citizenship and eligibility for a U.S. DoD Secret clearance, with ability to obtain and maintain Top Secret, SCI, and/or SAP-level access.
Nice-to-haves
- Experience with human-machine teaming, MUM-T, human-robot interaction, or applied artificial intelligence in mission autonomy applications such as UAV Groups 1–5.
- Experience with developmental or operational test and evaluation, including OITL and LVC testing.
- Scenario design and modeling and simulation experience.
- Familiarity with trust and reliance measurement and robustness, resilience, degraded, or off-nominal scenario testing.
- Experience with mission planning, C2, battle management, ground control stations, or HMIs.
- Familiarity with traceability methods or AI assurance frameworks.
- Willingness to use agentic AI to accelerate product development.
- Prior work with military operators, pilots, or subject matter experts, or an aircrew background.
Skills
Human-Machine Teaming, Human Factors, Human Performance Theory, Cognitive Task Analysis, Experimental Design, Statistical Analysis, Spss, R, Python, Operator-In-The-Loop Testing, Live-Virtual-Constructive Testing, Modeling And Simulation, Trust Measurement, Ai Assurance
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