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Human Machine Teaming Jobs (NOW HIRING)

Makai Labs LLC

Senior Software Engineer

New York, NY · On-site +1

$120K - $150K/yr

People are essential for all of our human-machine teaming solutions, as they serve as the final firewall for accuracy and quality. About the role This is a full-time remote role for a Senior Software ...

Makai Labs

Senior Software Engineer

New York, NY · On-site

$134K - $176K/yr

People are essential for all of our human-machine teaming solutions, as they serve as the final firewall for accuracy and quality. About the role This is a full-time remote role for a Senior Software ...

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Human Machine Teaming information

What is human machine teaming?

Human Machine Teaming refers to the collaboration between humans and artificial intelligence (AI) systems, robots, or other machines to achieve shared goals. This partnership leverages the complementary strengths of humans—such as creativity, judgment, and adaptability—and machines, which excel at processing large amounts of data quickly and performing repetitive tasks. The goal is to improve decision-making, efficiency, and outcomes in various industries, including defense, healthcare, manufacturing, and more. Effective human machine teaming requires thoughtful design of interfaces, clear communication protocols, and ongoing training for both humans and machines to work together seamlessly.

What skills and qualifications are needed for human machine teaming?

To thrive as a Human-Machine Teaming Specialist, you need expertise in human factors engineering, systems integration, and data analysis, often supported by a background in computer science, engineering, or cognitive psychology. Familiarity with AI platforms, machine learning tools, and human-computer interaction (HCI) frameworks is typically required. Strong collaboration, problem-solving, and communication skills help bridge the gap between human users and advanced technologies. These capabilities are crucial to designing seamless interactions, ensuring safety, and optimizing the joint performance of human and machine teams.

What are common challenges in human machine teaming and how can they be addressed?

Professionals in Human Machine Teaming often encounter challenges such as balancing effective communication between humans and AI systems, ensuring trust in automated processes, and integrating new technologies into existing workflows. Addressing these challenges requires continuous learning, active collaboration with multidisciplinary teams, and clear communication of complex technical concepts to non-technical stakeholders. Regular training, user feedback loops, and staying updated on advancements in AI and human factors engineering can help professionals navigate and overcome these obstacles successfully.
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Infographic showing various Human Machine Teaming job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 1% Temporary, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution.

Senior Engineer, Human Machine Teaming (R5649)

Shield AI

Washington, DC

$118K - $162K/yr

Full-time

Posted 14 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI's technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:

The Human Machine Teaming (HMT) Group at Shield AI is hiring an Engineer II or Senior Engineer to join our HMT Experimentation capability. At Shield AI, HMT refers to the design, management, and assurance of the adaptive relationships between operators and Hivemind-enabled mission autonomy-not just an interface problem, or a function-allocation exercise.

Working alongside the HMT Experimentation Lead, who owns HMT experimentation, research, and assessment, you will assist in establishing the HMT Experimentation Lab and help run the applied research and development (R&D) program behind our HMT design decisions. You will test whether collaborative work requirement profiles-the adaptive relationships-hold in practice, and conduct robustness testing that establishes where teaming works, degrades, and approaches failure.

If rigorous applied HMT-specific experimentation on in-development and fielded autonomous systems is what you want, this is your opportunity to make a lasting impact.

What you'll do:
  • 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 trust, prepare research protocols, and analyze human-machine system data.
  • 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%).
Required qualifications:
  • 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. Senior Engineer: typically requires a minimum of 3-5 years of related experience with a Bachelor's degree; or 2-4 years and a Master's degree; or 2 years with a PhD; or equivalent work 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 analyses and tools (e.g., SPSS, R, Python), and ability to translate results into design recommendations.
  • 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.
Preferred qualifications:
  • 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.
  • Experience in scenario design, and with modeling and simulation tools and methods.
  • Familiarity with trust and reliance measurement and experience with robustness, resilience, or degraded and off-nominal scenario testing.
  • Experience with mission planning, C2, and battle management concepts, processes, and doctrine, and with ground control stations or HMIs.
  • Familiarity with traceability methods, or with AI assurance frameworks.
  • Willingness to use agentic AI to speed the path from design concept to fielded product.
  • Prior work with military operators, pilots, or subject matter experts, or an aircrew background.
  • U.S. DoD Secret clearance eligible, with the ability to obtain and maintain Top Secret, SCI, and/or SAP-level access. U.S. citizenship required.
$140,000 - $210,000 a year
#LI-DM2
#LC
Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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