Machine Learning Engineer Intern (Privacy and Data Protection Office) - 2026 Start (PhD)

TikTok
San Jose, California

About the job

PDPO(Privacy and Data Protection Office) is the organization to lead, supervise, and empower all TikTok'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 TikTok's products and platforms. We are looking for talented individuals to join us for an internship in 2026. Internships at TikTok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at TikTok. PhD internships at TikTok 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.

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.

Qualifications

Minimum

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 NumPy, SciPy, Pandas, Scikit-learn, dplyr, or ggplot2

Preferred

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, TensorFlow, Keras or Theano.

Experience with Large Language Model is a plus.