Cyberdyne Systems
CAREERS
"Engineering the Evolution of Intelligence"
Cyberdyne Systems is not just a company; it is a collective of the world’s most elite minds.
We do not look for employees; we look for pioneers willing to push the boundaries of neural-net processing and autonomous robotics.
The Selection Process
Our recruitment process is designed to be the most rigorous in the defense industry.
We prioritize efficiency, logic, and physical resilience.
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Phase 1: Cognitive Assessment:Candidates must score in the top 0.01% of the Stanford-Binet or equivalent internal psychometric evaluations.
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Phase 2: Technical Defense Review:A 48-hour deep-dive into microprocessor architecture and heuristic learning models under the supervision of the Special Projects Division.
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Phase 3: Biometric & Physical Screening:All full-time candidates must undergo a comprehensive physical evaluation at our Sunnyvale campus to ensure "Operational Readiness."
Current Openings (Full-Time)
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Heuristic Logic Architect:Specializing in self-correcting neural pathways.
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Hyper-Alloy Metallurgist:Researching high-durability chassis materials for "Project Angel."
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Signal Intelligence Analyst:Monitoring global data streams for the SAC-NORAD network.
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Autonomous Systems Engineer:Developing independent tactical decision-making algorithms.
How to Apply
In-Person Applications Only.
Cyberdyne Systems does not accept digital resumes for full-time professional positions due to the sensitive nature of our DOD contracts.
Interested parties must report to the Cyberdyne Systems Security Kiosk at 18144 El Camino Real, Sunnyvale, CA, for an initial biometric scan and security vetting.
NOTICE
Cyberdyne Systems is an equal opportunity employer, though we prioritize candidates with previous experience in SAC-NORAD systems or advanced cybernetics.
The "Internship" Alternative
Can't make it to Sunnyvale?
For those who possess raw talent but lack the professional credentials or physical proximity to our California facilities, we offer the Cyberdyne Remote Internship Program.
This allows "Interns" to contribute to our neural-network training from their own terminals.