Machine Learning Intern – PhD
Content + Source + Freshness • 16 Dec 2025 • 95% confidence
Offer value
The internship offers essential experience in machine learning, suitable for PhD candidates, but limited in remuneration.
- Chance to work on advanced machine learning projects
- Gain hands-on experience in tech at Dropbox
- Lower intern stipend compared to industry norms
Pros
- Exposure to cutting-edge machine learning applications
- Collaboration with experienced teams at a well-known tech company
- Opportunity to contribute to real projects that impact products
Cons
- Lower stipend compared to industry standards for interns
- Expectations for high autonomy may be stressful
- Requires a significant commitment of time for research and development
Who it's for
Graduate / Postgraduate • Remote
Good fit
- PhD students in AI or related fields
- Tech-savvy individuals eager to apply theoretical work
- Collaborative researchers who thrive in innovative environments
Not recommended for
- Undergraduates or those without significant ML exposure
- Professionals looking for high compensation as interns
- Individuals needing heavily structured mentorship
Motivation fit
Key skills
About the job
• 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.
🔍 ATS Optimization Keywords
Below are skills and terms extracted directly from this job posting to improve Applicant Tracking System (ATS) visibility. This unique feature helps candidates tailor their applications more effectively — a feature exclusive to JobTailor job listings.
Hard Skills
- machine learning
- Python
- PyTorch
- scikit-learn
- Natural Language Processing
- Deep Learning
- Recommender Systems
- Learning to Rank
- Speech Processing
- Graph Learning
Soft Skills
- analytical skills
- problem-solving skills
- communication skills
- collaboration skills
- curiosity
- drive
