The Leidos Cyber Accelerator is seeking a hands-on applied researcher to design, execute, and automate real-world offensive security assessments while advancing ML-driven approaches to penetration testing. You will perform end-to-end automation of pentesting/red teaming (scoping → exploitation → post-exploitation → reporting), build repeatable tooling and test harnesses, and explore machine learning and reinforcement learning (RL) techniques for improving attack planning, prioritization, and autonomous decision-making.
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Job Type
Full-time
Career Level
Mid Level