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Internship Meta Data Science Jobs in Massachusetts

Meta

Competitive Intelligence Lead

Boston, MA

$177K/yr

As a Competitive Intelligence Lead in Meta's Competitive Intelligence organization, you will operate at the intersection of advanced analytics, data science, and market strategy. You will lead major ...

Smith & Nephew

Director, Clinical Data & AI

Andover, MA · On-site

Cross-study insights and meta-analyses * Drive integration of AI into core workflows, not point ... Oversee collaboration between data science, statistics, and programming teams 4. Synthetic Data ...

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Internship Meta Data Science jobs near you

Internship - Data Management

QuEra Computing, Inc.

Boston, MA

$30 - $40/hr

Internship

Re-posted 19 days ago

Job description

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. We are looking for the Photonics Data Engineer Intern to join us for Fall 2026.

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, Physics, Mathematics, or a related discipline.
  • Strong proficiency in Python programming, with hands-on experience using AI and data science libraries including PyTorch, NumPy, SciPy, and Pandas, and familiarity with workflow automation tools.
  • Working knowledge of data storage formats, database design principles, and data analysis and visualization frameworks.
  • Proven track record of leveraging Python and AI tools to tackle challenging problems in science and physics.
  • Strong analytical mindset with exceptional problem-solving capabilities.
  • Excellent interpersonal and communication skills, with the ability to collaborate effectively across multidisciplinary teams.
  • Clear evidence of self-motivation and the ability to drive independent projects to completion.
  • While a deep background in quantum physics is not a prerequisite, a solid understanding of computer science and mathematics in the context of physical simulation and experimental analysis is required.

Compensation Range: $30-$40/hr

On-site internship. There is no relocation offered for this role.

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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