Do you want to make an impact on quantum computing hardware development through computational science and engineering? Do you thrive when working with scientists and engineers from diverse backgrounds in a multidisciplinary environment? The Amazon Center for Quantum Computing (CQC) is seeking to hire an Applied Science Manager to help lead a team in the development and testing of novel superconducting quantum devices.
Work of the Device R&D team spans a broad spectrum of technical areas, including quantum and microwave electronics, semiconductor and superconducting device physics, nano- and micro-fabrication, and materials science. The work of the R&D team involves both fail-fast, exploratory work, as well as device engineering and functional yield testing/analysis. A Senior Applied Science Manager on the Device R&D team must have a broad technical base, covering the theory and physics of semiconductor and superconducting devices, precision measurement of qubits, device fabrication, and materials science. For this specific role we are looking for someone who has deep expertise in precision electronic measurement at the quantum level, and who can help lead our efforts to measure qubits, resonators, and other superconducting components. They should have deep technical knowledge of low-noise electrical measurements at cryogenic temperatures. We are also looking for someone with experience in device yield analysis techniques, and who has a strong device physics background and can work with our theory team to optimize the performance of our devices. In addition to expertise in test and measurement and device theory, the ideal candidate will have experience in device fabrication and materials characterization.
Key job responsibilities
Key job responsibilities
- Hire and develop Applied Scientists that build physical design and simulation software
- Partner with science teams to understand needs and drive adoption of improved methods and tooling
- Influence engineering team development priorities in high-performance computing infrastructure
- Manage tactical and strategic initiatives with scientific projects pursued within team
- Enable creative and innovative experimentation while striving for operational excellence
BASIC QUALIFICATIONS
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 3+ years of scientists or machine learning engineers management experience
- Experience programming in Java, C++, Python or related language
PREFERRED QUALIFICATIONS
- Experience hiring and growing top talent
- Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- Experience building complex highly-scalable systems that involve predictive models or applications of machine learning
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Knowledge of any of the following: computational electromagnetics, cryogenic electronics, VLSI physical design, electronic design automation, numerical modeling and simulation, superconducting qubits and quantum computing
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Pasadena - 183,800.00 - 248,700.00 USD annually
