Software Developer for Quantum and Photonic Devices

1 month ago

Ann Arbor, Michigan, United States Rydberg Technologies Full time
Job Title: Software Engineer for Quantum and Photonic Devices

Rydberg Technologies is seeking a highly skilled and experienced Software Engineer to join our team in the development and integration of software solutions for our cutting-edge quantum and photonic devices.

Key Responsibilities:
  • Design, develop, and maintain software for hardware devices, including control systems, signal processing algorithms, and user interfaces.
  • Implement solutions across the full technology stack, from low-level hardware interfaces to high-level application software.
  • Collaborate with physicists, hardware and electrical engineers to integrate electronic controls, optimize performance, and ensure seamless operation of prototypes and devices.
  • Develop and refine signal processing techniques to enhance device accuracy and performance.
  • Stay abreast of the latest advancements in software and embedded systems, quantum and photonics technology, and electrical engineering, contributing to innovative solutions and improvements.
  • Work closely with cross-functional teams, including physicists, engineers, and researchers, to achieve project goals and deliver high-quality products.
  • 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.

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