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Test Automation Python Engineer

Job Description - Test Automation Python Engineer

Quantum Machines is a global leader in control systems for quantum computing, a field on the verge of exponential growth.  

Our innovative hardware and software mark a groundbreaking approach in quantum computer control, scaling from individual qubits to expansive arrays of thousands. 

At the core of QM lies a passionate and ambitious team committed to reshaping the construction and operation of quantum computers. Our work is fueled by a deep understanding of customer needs, driving us to deliver unparalleled solutions in this revolutionary field. 

We are looking for a Senior Test Automation Engineer to join our Product Engineering Team. In this role, you will be responsible for designing and implementing automated test programs for hardware validation and production testing. You will work closely with hardware engineers to define test strategies, ensure seamless SW-HW integration, and optimize test environments to improve efficiency and reliability.

Key Responsibilities

  • Develop and maintain automated test programs for hardware validation and production testing.
  • Collaborate with hardware engineers to define, implement, and stabilize automated test environments.
  • Enable HW operation through software-driven testing methodologies.
  • Debug SW-HW integration issues and optimize test sequences for robustness and efficiency.
  • Maintain test documentation, analyze test results, and contribute to yield improvement efforts.

Required Qualifications

  • 1-3 years of experience in hardware test automation, SW-HW integration, and debugging.
  • Proficient in object-oriented programming, CI/CD, GIT and fluent in Python.
  • Experience with embedded systems testing and low-level hardware interfaces (I2C, SPI, UART, etc.).
  • Familiarity with test equipment such as oscilloscopes, power supplies, and signal analyzers.
  • Bachelor's degree in Electrical/Computer Engineering or a related field.

Preferred Qualifications

  • Knowledge of production testing workflows and data analysis for yield improvement.
  • Analyze hardware schematics and component datasheets to understand DUT (Device Under Test) behavior.
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