Machine Learning Intern – PhD

November 5

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Dropbox

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Cloud Storage • Enterprise • Productivity

Dropbox is a cloud-based service that provides tools for storing, sharing, and accessing files across devices. It offers features such as document sharing, video review, automatic backups, and AI-driven scheduling. Dropbox also provides solutions for different sectors like teams, sales, marketing, and education, and industries including construction, media, technology, and manufacturing. With a focus on security, Dropbox ensures files are encrypted and protected against tampering. It offers integrations with various productivity tools and is trusted by major companies for efficient file management and collaboration.

1001 - 5000 employees

Founded 2007

🏢 Enterprise

⚡ Productivity

📋 Description

• Research and prototype innovative machine learning approaches in areas such as Search, Large Language Models (LLMs), Multimodal Content Understanding, and Recommender Systems • Design and implement end-to-end ML pipelines—from data exploration to model training, evaluation, and deployment—in collaboration with mentors and product teams • Analyze large-scale datasets to identify opportunities for personalization and improved user experiences • Partner with Product, Design, and Engineering teams to integrate models into Dropbox products • Contribute to the team’s technical discussions, offering research-based perspectives to guide experimentation and long-term strategy

🎯 Requirements

• Currently pursuing a PhD in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field, with a research focus on advanced AI • Graduation date in Winter 2027 or Spring/Summer 2028. • Proven experience in applied AI, through research publications, significant projects, or internships where you built or tested advanced ML solutions. • Strong coding skills (e.g., Python, PyTorch, scikit-learn, or similar ML libraries), plus an ability to quickly prototype and iterate on cutting-edge ideas. • Curiosity and drive to explore novel ML methodologies and translate them into practical applications that solve user needs. • Research experience in one or more of the following: Natural Language Processing, Large Language Models, Deep Learning, Recommender Systems, Learning to Rank, Speech Processing, Graph Learning. • Strong analytical and problem-solving skills, with the ability to bridge research and practical application. • Excellent communication and collaboration skills, especially in interdisciplinary teams. • Familiarity with modern ML infrastructure and large-scale data systems.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off