Software Development Engineer II, Centre for Quantum Computing
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Description
The Center for Quantum Computing (CQC) is hiring a Software Development Engineer to build AI-native systems that accelerate quantum device research and fabrication. You will work at the intersection of software engineering, machine learning, and experimental science, building workflows and data infrastructure that connect scientists, hardware engineers, and AI models into a tightly integrated development loop.
Key job responsibilities
- Design and build data lakes and pipelines that unify experimental, fabrication, and metrology data from heterogeneous sources into a single, queryable platform for scientists and engineers
- Develop AI-native workflows that automate the experiment-analysis-recommendation cycle: ingest results, run ML models, surface insights, and propose next steps with minimal human intervention
- Build LLM-powered tools and autonomous agents that allow researchers to query, visualize, and reason over fabrication and experimental data using natural language
- Partner directly with research scientists, process engineers, and hardware teams to understand their problems deeply and translate research needs into working software
- Implement ML-driven analysis systems (e.g., automated defect detection, yield prediction, process optimization) that operate on live fabrication data
- Design and build recommendation engines that evaluate design-of-experiment tradeoffs (cost, time, performance) and surface actionable suggestions to research teams
- Own the reliability, scalability, and operational health of the systems you build, including monitoring, alerting, and on-call support
- Contribute to the technical direction of the Device Lifecycle team through design documents, architecture reviews, and code reviews
About the team
You will be joining the Device Lifecycle software development team within the AWS Center for Quantum Computing. Our team builds the software that enables scaling up quantum computing technologies, from fabrication execution systems to AI-powered research tools. We are a small, high-impact team where every engineer's work directly shapes the pace of quantum device development.
Key job responsibilities
- Design and build data lakes and pipelines that unify experimental, fabrication, and metrology data from heterogeneous sources into a single, queryable platform for scientists and engineers
- Develop AI-native workflows that automate the experiment-analysis-recommendation cycle: ingest results, run ML models, surface insights, and propose next steps with minimal human intervention
- Build LLM-powered tools and autonomous agents that allow researchers to query, visualize, and reason over fabrication and experimental data using natural language
- Partner directly with research scientists, process engineers, and hardware teams to understand their problems deeply and translate research needs into working software
- Implement ML-driven analysis systems (e.g., automated defect detection, yield prediction, process optimization) that operate on live fabrication data
- Design and build recommendation engines that evaluate design-of-experiment tradeoffs (cost, time, performance) and surface actionable suggestions to research teams
- Own the reliability, scalability, and operational health of the systems you build, including monitoring, alerting, and on-call support
- Contribute to the technical direction of the Device Lifecycle team through design documents, architecture reviews, and code reviews
About the team
You will be joining the Device Lifecycle software development team within the AWS Center for Quantum Computing. Our team builds the software that enables scaling up quantum computing technologies, from fabrication execution systems to AI-powered research tools. We are a small, high-impact team where every engineer's work directly shapes the pace of quantum device development.
