Qubit Characterization Engineer

At IBM Research, we are the innovation engine of IBM. Exploring what’s next in computing and shaping the technologies the world will rely on tomorrow. From advancing AI and hybrid cloud to pioneering practical quantum computing, we anticipate challenges and unlock new opportunities for clients, partners, and society. Working in Research means joining a team that accelerates discovery at the intersection of high-performance computing, AI, quantum, and cloud. You’ll collaborate with leading scientists, engineers, and visionaries to push boundaries and turn ideas into reality. With a culture built on curiosity, creativity, and collaboration, IBM Research offers the opportunity to grow your career while contributing to breakthroughs that transform industries and change the world. Characterize superconducting qubits and devices through cryogenic measurements, including coherence, relaxation, spectroscopy, and two-qubit gate performance. Develop and execute measurement experiments using RF/microwave instrumentation, dilution refrigerators, and automated data-acquisition systems; analyze data to identify device and process limitations. Collaborate with fabrication, design, and software teams to diagnose device performance issues, improve qubit yield and quality, and translate characterization results into actionable hardware improvements. BS or MS in Physics, Electrical Engineering, Applied Physics, or a related technical field, with hands-on experience in experimental quantum hardware, microwave/RF measurements, or cryogenic systems. Proficiency with laboratory instrumentation, data acquisition, and analysis; ability to troubleshoot complex experimental systems and communicate results effectively across multidisciplinary engineering teams. Experience characterizing superconducting qubits and/or microwave devices, including spectroscopy, coherence measurements (T1/T2), resonator measurements, and analysis of qubit performance. Basic proficiency with AI/ML tools for data analysis, experiment automation, troubleshooting, and improving engineering workflows; familiarity with tools such as Python-based AI/ML libraries or generative AI assistants is a plus.