Evaluate different quantum computing qubit technologies to identify system bottlenecks and key trade-offs Construct performance models and determine optimal system requirements Develop advanced toolsets for modeling quantum components Determine novel quantum applications and evaluate the quantum resources needed to execute them on a quantum system architecture Conceptualize and design the subsystems of the complex architecture that defines the quantum machine Bachelor's degree in Computer Science, Mathematics, Physics, Physical Sciences, Computer Engineering, Software Engineering, or related field AND 8+ years experience, including research and/or development of commercial software, compilers, scientific computing applications, or multi-component systems OR Master's degree in Computer Science, Mathematics, Physics, Physical Sciences, Computer Engineering, Software Engineering, or related field AND 6+ years experience, including research and/or development of commercial software, compilers, scientific computing applications, or multi-component systems OR Doctorate in Computer Science, Mathematics, Physics, Physical Sciences, Software Engineering, or related field AND 3+ years experience, including research and/or development of commercial software, hardware engineering, compilers, scientific computing applications, or multi-component systems OR equivalent experience. 4+ years of experience in one or more of the following areas: high-performance computing, quantum algorithms, quantum error correction, quantum simulation, hardware accelerator simulation and/or modeling. Demonstrated ability to work effectively across internal and external organizations, with strong communication and leadership skills. Ability to leverage AI tools to drive innovation and efficiency (e.g., performance modeling and analysis, research gathering, day to day task automation). Experience developing and implementing algorithms for quantum applications, preferably for fault-tolerant quantum systems. Experience with classical computer performance modeling and architecture including accelerators (GPUs, TPUs, or coprocessor designs) Experience with high-performance classical computing methods. Skills in applied mathematics or related disciplines. Methodical problem-solving and critical-thinking abilities. Proficient written and verbal communication skills. Ability to work independently and collaboratively within a dynamic multi-disciplinary team environment.
