Amazon FPGA Engineer AWS Center Quantum Computing 

United States, California, Pasadena 

680807320

We are looking for an FPGA Engineer to contribute to our quantum control platform. As a part of the control stack team, you will develop and integrate RTL designs and embedded software with an eye towards overcoming novel challenges in experimental quantum computing, such as high-throughput device characterization & calibration, or enabling real-time quantum error correction protocols. The ideal candidate will help us work backwards from our broader experimental goals, driving improvements to our control platform at the hardware/software interface while ensuring that high-level requirements (e.g. latency, bandwidth, resource utilization) are met.This position is on-site at our lab, located on the Caltech campus in Pasadena, CA.
Key job responsibilities
- Work with stakeholders to understand and refine hardware/software requirements.
- Propose architectural or micro-architectural updates to our control platform to meet requirements.
- Implement RTL subsystems in Verilog or SystemVerilog.
- Develop embedded software in C, C++ or Rust for high-performance near-real-time tasks.
- Verify & validate designs, both in simulation and in bench-top / real-world conditions.
- Ensure new features are successfully integrated into our Python-based experimental software stack.A day in the life
The majority of your time will be spent on projects that extend the functional capabilities or performance of our existing control platform. This requires working backwards from the needs of our science staff in the context of our larger experimental roadmap. You will translate hardware and software requirements into design proposals balancing implementation complexity against time-to-delivery. Once a design proposal has been reviewed and accepted, you will drive the implementation and coordinate with internal stakeholders to ensure a smooth roll out. Because many high-level experimental goals have cross-cutting requirements, you’ll often work closely with other software or hardware engineers on the team.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance
Export Control Requirement:
Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

- Bachelor's degree or equivalent
- 3+ years of non-internship professional FPGA development experience using Verilog/VHDL or equivalent
- 2+ years of experience developing embedded software in C, C++, or Rust
- Experience with a scripting language (bash, TCL, Python, etc)
- Experience performing hardware bring-up/debugging
- Experience with standard communication interfaces (e.g. USB, PCIe, Ethernet)

- M.Sc. degree, or equivalent, in Electrical Engineering, Computer Engineering, Physics, or Computer Science
- Experience with soft core RISC-V implementation
- Experience with Xilinx SoC platforms
- Experience with high-level synthesis tools
- Experience developing real-time operating system (RTOS) applications
- Experience with low-level device driver and kernel development (esp. on Xilinx MPSoC or other ARM architectures)
- Experience with high-performance networking technologies (e.g. DPDK, RDMA)
- Experience with low-latency distributed computation
- Knowledge of Linux kernel internals and networking or storage subsystems architecture