Senior Quantum Error Correction Scientist — FTQC

Amazon; Seattle (WA); On-site; USD 167,000 - 249,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Braket is seeking a Senior Applied Scientist with deep expertise in quantum error correction to work on compilation science, building fault-tolerant quantum capabilities.

You will map logical circuits to physical qubits, optimize resource usage, and integrate decoders into execution flows, collaborating with the FTQC Science Lead to translate research into production software and scalable infrastructure.

Qualifications

• PhD in physics, CS, applied mathematics or related field with focus on quantum information science.
• 3+ years of research experience in quantum error correction (academic or industry).
• Experience implementing quantum algorithms or error correction protocols in simulation or on real hardware.

Responsibilities

• Drive scientific design decisions for fault-tolerant quantum workloads: error correction code selection, logical gate synthesis, and qubit mapping strategies
• Develop and implement resource estimation algorithms that guide compilation optimization
• Collaborate with software engineers to translate QEC research into production software
• Benchmark approaches against realistic hardware noise models and device constraints
• Work with quantum hardware providers on compilation strategies tailored to specific architectures
• Publish research in coordination with the broader Braket science team, representing Amazon Braket at relevant conferences and workshops

Skills

C/C++

Python

Java

Perl

Education

PhD in Physics, Computer Science, Applied Mathematics, or related field

Tools

Stim

PyMatching

TKET

Job description

Amazon Braket is seeking a Senior Applied Scientist with deep expertise in quantum error correction to work on compilation science, building fault-tolerant quantum capabilities.

You will map logical circuits to physical qubits, optimize resource usage, and integrate decoders into execution flows, collaborating with the FTQC Science Lead to translate research into production software and scalable infrastructure.