Key responsibilities include:

• Designing tactical autonomy algorithms to enable unmanned aircraft to perform complex missions
• Developing high-performance software modules that incorporate planning, decision-making, and behavior execution strategies
• Implementing and testing behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios
• Working at the intersection of classical autonomy and machine learning, blending rule-based systems with learning-based methods such as reinforcement learning to achieve robust, adaptive behavior
• Collaborating with cross-functional teams to ensure seamless integration of autonomy solutions on real-world platforms
• Deploying autonomy capabilities to real platforms and participating in field tests and flight demos, validating performance in operationally relevant conditions
• Analyzing mission logs and performance data to diagnose failures, optimize behavior models, and inform iterative development

Required qualifications include:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS)
• Significant background in robotics technologies related to motion planning, behavior modeling, decision-making, or autonomous system design
• Significant experience with unmanned system technologies and accompanying algorithms (specifically air domain)
• Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation

Preferred qualifications include:

• Experience applying ML/RL techniques in autonomy pipelines
• Background in collaborative behaviors, swarm robotics, or distributed decision-making
• Familiarity with tactical behaviors for unmanned systems in DoD or government programs

Salary: $160,000 - $240,000 a year

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Key responsibilities include:

• Designing tactical autonomy algorithms to enable unmanned aircraft to perform complex missions
• Developing high-performance software modules that incorporate planning, decision-making, and behavior execution strategies
• Implementing and testing behavior architectures that enable multi-agent coordination, target engagement, reconnaissance, and survivability in contested scenarios
• Working at the intersection of classical autonomy and machine learning, blending rule-based systems with learning-based methods such as reinforcement learning to achieve robust, adaptive behavior
• Collaborating with cross-functional teams to ensure seamless integration of autonomy solutions on real-world platforms
• Deploying autonomy capabilities to real platforms and participating in field tests and flight demos, validating performance in operationally relevant conditions
• Analyzing mission logs and performance data to diagnose failures, optimize behavior models, and inform iterative development
• Contributing to the autonomy roadmap by researching and prototyping new algorithms, identifying tactical capability gaps, and proposing novel solutions that advance Shield AI's mission

Requirements include:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience
• Proficiency in programming languages such as C++ and Python, and familiarity with real-time operating systems (RTOS)
• Significant background in robotics technologies related to motion planning, behavior modeling, decision-making, or autonomous system design
• Significant experience with unmanned system technologies and accompanying algorithms (specifically air domain)
• Experience with simulation tools and environments (e.g., AFSIM, NGTS) for testing and validation
• Strong problem-solving skills, with the ability to troubleshoot and optimize system performance
• Excellent communication and teamwork skills, with the ability to work effectively in a collaborative, multidisciplinary environment
• Ability to obtain a SECRET clearance

Preferred qualifications include experience applying ML/RL techniques in autonomy pipelines, background in collaborative behaviors, swarm robotics, or distributed decision-making, familiarity with tactical behaviors for unmanned systems in DoD or government programs, and hands-on experience supporting flight demos or live exercises.

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