Senior Engineer, Human-Machine Teaming & Autonomy

Shield AI

Washington

On-site

USD 140,000 - 210,000

Full time

14 days+
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Job summary

Shield AI is seeking an Engineer II or Senior Engineer to join the Human Machine Teaming (HMT) Experimentation capability. You will help establish the HMT Experimentation Lab and run applied R&D to inform design decisions for HMT systems, including robustness testing and operator performance evaluation.

You will design experiments, assess collaboration profiles, and translate results into actionable recommendations.

Qualifications

  • Degree in human factors, psychology, cognitive systems engineering, or related field.
  • Engineer II or Senior Engineer path with required experience.
  • Strong knowledge of human machine teaming and performance measurement.
  • Experience with experimental design and data analysis tools.
  • Ability to translate results into design recommendations.

Responsibilities

  • Design and run HMT experiments to test collaborative work profiles.
  • Conduct robustness testing across communications, sensors, autonomy, workload.
  • Characterize context sensitivity of requirements across environments.
  • Extend OITL and LVC testing for HMT experimentation.
  • Define quantitative/qualitative performance measures; build assessment batteries.
  • Translate findings into prioritized recommendations for development.
  • Report results to engineering and customer audiences.
  • Travel to test sites and customers (approx. 25%).

Skills

HMT expertise
Experimental design
Statistics (multivariate)
Python/R/SPSS
Teamwork & communication

Education

Bachelor’s degree in a related field

Tools

SPSS
R
Python

Job description

Shield AI is seeking an Engineer II or Senior Engineer to join the Human Machine Teaming (HMT) Experimentation capability. You will help establish the HMT Experimentation Lab and run applied R&D to inform design decisions for HMT systems, including robustness testing and operator performance evaluation.

You will design experiments, assess collaboration profiles, and translate results into actionable recommendations.

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