Internship – Data Management

Benefits

Parental leave

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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About this role

Internship – Data Management Boston, MA, USA About QuEra Computing, Inc. QuEra Computing is building the world's most powerful neutral-atom quantum computers. Our systems are designed to scale and enable groundbreaking advances in science and technology. We collaborate closely with leading academic and industry partners to push the boundaries of quantum computing, error correction, and fault tolerance. Summary The Photonics team at QuEra pioneers cutting-edge photonic chips for integration into neutral-atom quantum computers. QuEra Computing Inc. seeks a Photonics Data Engineer Intern to develop an AI-powered data infrastructure that supports our design, fabrication, and testing workflows. You'll develop tools that transform raw measurement and metrology data into actionable insights, directly informing how we design better photonic chips faster for large-scale neutral atom quantum computers. Responsibilities - AI-powered Data Infrastructure: Develop an AI-powered data management infrastructure for photonic integrated circuit (PIC) design, fabrication, and testing workflows. - Automation and Tooling: Write Python functions and utilities to automate data ingestion, cleaning, and organization across multiple data sources. - Performance Analysis Pipelines: Build analysis pipelines to extract key device performance metrics (e.g., insertion loss, extinction ratio, bandwidth, yield). Analyze fabrication metrology datasets from multiple foundries and correlate findings with device performance to identify process-performance relationships. - Cross-functional Collaboration: Work with other photonics engineers to define data schemas and best practices for reproducible design and testing workflows. - Documentation: Document data infrastructure and analysis workflows for long-term team use. Qualifications - Currently pursuing or recently completed a Bachelor's or Master's degree in Computer Science,

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