Software Engineer (Quantum and Photonics)
Rydberg Technologies
Software Engineering
Ann Arbor, MI, USA
Posted on Mar 20, 2026
Rydberg Technologies is seeking a dynamic and experienced Software Engineer for quantum and photonic devices. This is a hands-on role in the development and integration of software solutions for our cutting-edge quantum and photonic devices and technology. You will work across the full stack, from hardware electronic controls to signal processing. The ideal candidate will bring broad expertise in software programming, electrical engineering, and background in physics to advance our technologies, products, and services.
Key Responsibilities include, but are not limited to:
Software Development: Design, develop, and maintain software for hardware devices, including control systems, signal processing algorithms, and user interfaces.Full-Stack Engineering: Implement solutions across the full technology stack, from low-level hardware interfaces to high-level application software.Hardware Integration: Collaborate with physicists, hardware and electrical engineers to integrate electronic controls, optimize performance, and ensure seamless operation of prototypes and devices.Signal Processing: Develop and refine signal processing techniques to enhance device accuracy and performance.Research and Innovation: Stay abreast of the latest advancements in software and embedded systems, quantum and photonics technology, and electrical engineering, contributing to innovative solutions and improvements.Team Collaboration: Work closely with cross-functional teams, including physicists, engineers, and researchers, to achieve project goals and deliver high-quality products.Documentation and Testing: Create comprehensive documentation for software systems and conduct rigorous testing to ensure reliability and robustness.
Competencies and Skills:
Embedded Systems Programming: Proficiency in C, C++, Python, specifically tailored to embedded systems. Experience in developing firmware for RF receivers, including real-time processing and low-level hardware interaction.Firmware Development: Skills in developing and optimizing firmware for controlling laser devices and quantum sensors.Real-Time Operating Systems (RTOS): Knowledge of RTOS for managing embedded systems efficiently.Data Acquisition and Processing: Techniques for acquiring, processing, and analyzing data from laser and quantum sensor systems.Digital Signal Processing (DSP): Techniques for implementing DSP algorithms on both general-purpose processors and specialized hardware like FPGAs and DSPs.Software Defined Radio (SDR): Familiarity with SDR platforms and tools such as GNU Radio, and skills in developing and optimizing SDR applications.Algorithm Development: Developing algorithms for signal processing, data analysis, and control systems. Developing and optimizing algorithms for RF signal acquisition, demodulation, decoding, and analysis.Control Theory: Understanding of feedback control systems and PID controllers for stabilizing lasers and quantum sensors.Microcontrollers and Microprocessors: Understanding of different types of microcontrollers (e.g., ARM Cortex) and microprocessors.Hardware-Software Integration: Skills in interfacing software with hardware components like sensors, actuators, and communication modules.Memory Management: Efficient use of memory and processing power in constrained environments. Control Signal Processing: Knowledge in processing signals from various sensors (e.g., photodetectors, temperature sensors, accelerometers, etc.).Communication Protocols: Familiarity with protocols like SPI, I2C, UART, and wireless communication standards (Bluetooth, Wi-Fi).Security: Implementing security measures in embedded systems to protect data and privacy.Laboratory Automation: Skills in automating experiments and measurements using platforms like MATLAB or LabVIEW.
Additional Skills:
Control Systems: Knowledge of feedback control systems for automatic gain control (AGC), frequency control, and other RF system parameters.RF Testing and Measurement: Experience with RF testing equipment like network analyzers, spectrum analyzers, signal generators, and oscilloscopes.Communication Protocols: Understanding of communication standards and protocols, such as Bluetooth, Wi-Fi, LTE, and 5G.Simulation and Modeling: Use of tools like HFSS, CST Microwave Studio, or ADS for simulating and modeling RF circuits and antenna systems.Machine Learning: Sound understanding and experience of machine learning algorithms, including supervised, unsupervised, and reinforcement learning.Deep Learning: Proficiency in neural networks, CNNs, RNNs, LSTMs, GANs, and other deep learning architectures.Data preprocessing: Skills in data cleaning, normalization, augmentation, and feature engineering.Model Training and Optimization: Experience with techniques for training models efficiently, hyperparameter tuning, and optimization. Debugging and Testing: Proficiency in debugging tools and techniques for both software and hardware, and experience with automated testing frameworks.Version Control: Use of version control systems for development.Project Management: Skills in managing projects with cross-disciplinary teams.Education: Keeping up-to-date with latest advancements in signal processing and embedded systems.
Qualifications:Bachelor's or Master’s degree in Computer Science, Physics, Electrical Engineering, or a related field. A PhD is a plus.Proven experience in software development for hardware devices or similar technologies. Expertise in full-stack development, electrical engineering, and signal processing is essential.Solid foundation in physics with experience working in quantum technologies, sensors, or related fields preferred but not required.Proficient in electrical engineering principles and practices, experience in circuit design, PCB layout, and hardware troubleshooting a plus.Track record of publications in peer-reviewed academic journals a plus.Exceptional analytical and problem-solving skills, with the ability to tackle complex technical challenges.Excellent problem-solving skills and attention to detail.Strong communication skills and the ability to work effectively in a multi-disciplinary and team-oriented environment.US citizens or green card holders may be given priority due to export controls.
Key Responsibilities include, but are not limited to:
Software Development: Design, develop, and maintain software for hardware devices, including control systems, signal processing algorithms, and user interfaces.Full-Stack Engineering: Implement solutions across the full technology stack, from low-level hardware interfaces to high-level application software.Hardware Integration: Collaborate with physicists, hardware and electrical engineers to integrate electronic controls, optimize performance, and ensure seamless operation of prototypes and devices.Signal Processing: Develop and refine signal processing techniques to enhance device accuracy and performance.Research and Innovation: Stay abreast of the latest advancements in software and embedded systems, quantum and photonics technology, and electrical engineering, contributing to innovative solutions and improvements.Team Collaboration: Work closely with cross-functional teams, including physicists, engineers, and researchers, to achieve project goals and deliver high-quality products.Documentation and Testing: Create comprehensive documentation for software systems and conduct rigorous testing to ensure reliability and robustness.
Competencies and Skills:
Embedded Systems Programming: Proficiency in C, C++, Python, specifically tailored to embedded systems. Experience in developing firmware for RF receivers, including real-time processing and low-level hardware interaction.Firmware Development: Skills in developing and optimizing firmware for controlling laser devices and quantum sensors.Real-Time Operating Systems (RTOS): Knowledge of RTOS for managing embedded systems efficiently.Data Acquisition and Processing: Techniques for acquiring, processing, and analyzing data from laser and quantum sensor systems.Digital Signal Processing (DSP): Techniques for implementing DSP algorithms on both general-purpose processors and specialized hardware like FPGAs and DSPs.Software Defined Radio (SDR): Familiarity with SDR platforms and tools such as GNU Radio, and skills in developing and optimizing SDR applications.Algorithm Development: Developing algorithms for signal processing, data analysis, and control systems. Developing and optimizing algorithms for RF signal acquisition, demodulation, decoding, and analysis.Control Theory: Understanding of feedback control systems and PID controllers for stabilizing lasers and quantum sensors.Microcontrollers and Microprocessors: Understanding of different types of microcontrollers (e.g., ARM Cortex) and microprocessors.Hardware-Software Integration: Skills in interfacing software with hardware components like sensors, actuators, and communication modules.Memory Management: Efficient use of memory and processing power in constrained environments. Control Signal Processing: Knowledge in processing signals from various sensors (e.g., photodetectors, temperature sensors, accelerometers, etc.).Communication Protocols: Familiarity with protocols like SPI, I2C, UART, and wireless communication standards (Bluetooth, Wi-Fi).Security: Implementing security measures in embedded systems to protect data and privacy.Laboratory Automation: Skills in automating experiments and measurements using platforms like MATLAB or LabVIEW.
Additional Skills:
Control Systems: Knowledge of feedback control systems for automatic gain control (AGC), frequency control, and other RF system parameters.RF Testing and Measurement: Experience with RF testing equipment like network analyzers, spectrum analyzers, signal generators, and oscilloscopes.Communication Protocols: Understanding of communication standards and protocols, such as Bluetooth, Wi-Fi, LTE, and 5G.Simulation and Modeling: Use of tools like HFSS, CST Microwave Studio, or ADS for simulating and modeling RF circuits and antenna systems.Machine Learning: Sound understanding and experience of machine learning algorithms, including supervised, unsupervised, and reinforcement learning.Deep Learning: Proficiency in neural networks, CNNs, RNNs, LSTMs, GANs, and other deep learning architectures.Data preprocessing: Skills in data cleaning, normalization, augmentation, and feature engineering.Model Training and Optimization: Experience with techniques for training models efficiently, hyperparameter tuning, and optimization. Debugging and Testing: Proficiency in debugging tools and techniques for both software and hardware, and experience with automated testing frameworks.Version Control: Use of version control systems for development.Project Management: Skills in managing projects with cross-disciplinary teams.Education: Keeping up-to-date with latest advancements in signal processing and embedded systems.
Qualifications:Bachelor's or Master’s degree in Computer Science, Physics, Electrical Engineering, or a related field. A PhD is a plus.Proven experience in software development for hardware devices or similar technologies. Expertise in full-stack development, electrical engineering, and signal processing is essential.Solid foundation in physics with experience working in quantum technologies, sensors, or related fields preferred but not required.Proficient in electrical engineering principles and practices, experience in circuit design, PCB layout, and hardware troubleshooting a plus.Track record of publications in peer-reviewed academic journals a plus.Exceptional analytical and problem-solving skills, with the ability to tackle complex technical challenges.Excellent problem-solving skills and attention to detail.Strong communication skills and the ability to work effectively in a multi-disciplinary and team-oriented environment.US citizens or green card holders may be given priority due to export controls.