QuEra Computing, Inc. - QPU Software Engineer
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Requirements
• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Physics, or a related field. • 5+ years of experience developing software for hardware control, embedded systems, or distributed systems. • Strong programming skills in Python and/or C/C++, and experience working with hardware interfaces (e.g., SPI, I2C, UART, Ethernet). • Python • C/C++ • Experience with real-time systems or hardware-in-the-loop control environments. • Familiarity with timing systems (e.g., PTP), and communication stacks. • Proficiency in system integration, testing, and performance tuning. • Experience with scientific instrumentation, lab automation, or quantum hardware control systems. • Familiarity with FPGA systems, DAC/ADC control, or pulse sequencing frameworks. • Exposure to embedded Linux, RTOS, or custom firmware development. • Knowledge of calibration, feedback, or control loop algorithms. • Experience in multidisciplinary teams working at the intersection of hardware, software, and science.
Responsibilities
• Design and implement software systems for orchestrating quantum experiments, including pulse sequence generation, device coordination, and real-time system control. • Develop and maintain APIs and middleware that connect hardware control layers (e.g., FPGA, DACs, timing systems) with higher-level orchestration software and compilers. • Implement reliable communication and synchronization protocols across embedded and distributed system components. • Collaborate with system architects and physicists to translate experimental requirements into testable, high-performance software features. • Contribute to diagnostic and calibration routines for hardware validation and performance monitoring. • Develop tooling to support automation, test infrastructure, system state management, and logging. • Participate in system bring-up, integration testing, and cross-disciplinary debugging efforts. • Contribute to software architecture decisions, code reviews, and best practices across the engineering team.
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