Machine Learning Engineer Intern; Privacy and Data Protection Office PhD

Responsibilities

PDPO(Privacy and Data Protection Office) is the organization to lead, supervise, and empower all Tik Tok's privacy work in an accountable and industry leading way. This team is the expert in the landscape of privacy risks and passionate about consulting across the company on implementing the proper safeguards and technical mitigations to ensure that our users’ privacy is honored across the Tik Tok's products and platforms.

We are looking for talented individuals to join us for an internship in 2026. Internships at Tik Tok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at Tik Tok.

PhD internships at Tik Tok provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts.

Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Responsibilities:

• Formulate end-to-end machine learning models by utilizing ML, NLP techniques to deal with real-world signals generated from privacy products/ incidents/ review areas.
• Analyze extensive, complex datasets to extract meaningful insights, identify opportunities for improvement, and facilitate data-driven decision-making.
• Design and execute experiments, testing and iterating on machine learning models to optimize recommendation functions and boost user satisfaction.
• Communicate final recommendations and drive decision making.

You will utilize data-driven techniques in building solutions to help measure, validate, identify, and envision Tik Tok's privacy evolution. You will design and scope out projects, build operationalized analytics tools and platforms, and most importantly, use data and AI models to find insights, diagnose problems and tell compelling stories.

Besides the technical side, you will also get the opportunity to work closely with various XFN teams, including but not limited to engineering, legal, audit, security, public, government relations, and products. You will be expected to build deep domain knowledge and build a strong domain expertise in privacy.

Qualifications

Minimum Qualifications:

• Master’s or PhD in Computer Science, Finance, Mathematics, Statistics, Operations Research or other related field
• Solid background in NLP and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods.
• Experience performing data extraction, cleaning, analysis and presentation for medium to large datasets
• Experience with at least one programming language (i.e. Python, R, Java, or C++)
• Experience writing SQL queries
• Experience with scientific computing and analysis packages such as Num Py, Sci Py, Pandas, Scikit-learn, dplyr, or ggplot2

Preferred Qualifications:

• Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
• Experience with data visualization libraries such as Matplotlib, Pyplot, ggplot2
• Experience with machine learning libraries and deep learning toolkits such as PyTorch, Caffe2, Tensor Flow, Keras or Theano.
• Experience with Large Language Model is a plus.

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Job Information

【For Pay Transparency】Compensation Description (Hourly) - Campus Intern

The hourly rate range for this position in the selected city is $60- $60.

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing…