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PhD Systems & AI/ML Research Intern (Summer 2026)

Dropbox

Remote - US: All locations (US) Remote permanent

Posted: January 28, 2026

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Job Description

Role Description

Dropbox powers collaboration and cloud infrastructure for over 700 million registered users worldwide. We’re building the next generation of scalable storage, distributed compute, large-scale content processing, and secure infrastructure, with AI/ML workloads top-of-mind.

As a PhD Systems & AI/ML Research Intern, you’ll work on meaningful infrastructure problems at the intersection of distributed systems, backend services, and AI/ML workloads. Supported by senior engineers, you’ll own a project aligned with your research, that results in a working prototype with the goal of a submission for adoption internally and external publication. Come help us define and build the infra layer for our next-gen products.

Responsibilities

• Execute a defined engineering/research project aligned with your research.

• Implement a prototype that addresses a concrete infrastructure or AI-systems challenge.

• Build and run benchmarks using realistic workloads to measure performance, reliability, or security improvements.

• Document the design and implementation, including assumptions, architecture, tradeoffs, and evaluation results.

• Deliver a final artifact that includes a working prototype, reproducible results, technical write-up, and internal presentation.

• Collaborate with mentors to refine the approach, validate results, and, if appropriate, prepare findings for internal adoption or external publication.

Requirements

• PhD candidate in Computer Science or a related field graduating between Winter 2026 and Spring 2028.

• Proven experience in systems/infrastructure and/or AI/ML through research publications, significant projects, or internships where you built or tested advanced solutions.

• Strong coding skills (e.g., Python, Rust, Go, C++) plus an ability to quickly prototype and iterate on cutting-edge ideas.

• Curiosity and drive to explore novel systems methodologies and translate them into practical applications that solve practical needs.

• Excellent communication and collaboration skills, especially in interdisciplinary teams.

Preferred Qualifications

• Prior systems publications, open-source contributions, or experience operating large-scale infrastructure

• Interest in translating research insights into product impact for real-world users

• Familiarity and passion for swiftly moving from idea to experiment, comfortable with ambiguous or evolving project goals

Compensation

US Pay Range
$12,500—$12,500 USD

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