Machine Learning Intern, Recommendation Systems

Job Description

Machine Learning Engineer Intern | TikTok

The Tone:
This is an internship at TikTok, available across its various global offices, with opportunities potentially located in Los Angeles. TikTok operates as the leading global destination for short-form mobile video, with a core mission to inspire creativity and bring joy to its users. This role within the central Recommendation algorithm team is crucial for driving significant product decisions and platform growth through supporting and innovating on production recommendation models, directly impacting user experience across the platform.

The TL;DR
• Role: Internship
• Type: Temporary (Summer Internship)
• Location: In-person, Los Angeles (inferred)
• Pay: $45 hourly
• Team: Recommendation organization, comprising machine learning researchers and engineers.
• Mission: To drive the development and optimization of industry-leading recommendation systems that elevate user experience, strengthen platform safety, and empower a vibrant content ecosystem.
• Tech Stack: PyTorch, TensorFlow, C/C++, Python, shell programming languages.

What You’ll Actually Do
• Develop: Drive the creation of industry-leading recommendation systems to enhance user experience, strengthen platform safety, and empower the content ecosystem.
• Deliver: Provide impactful, end-to-end machine learning solutions for high-priority product challenges such as content understanding, LLMs, robustness, and fairness.
• Optimize: Own and continuously refine the full-stack ML pipeline, from algorithm design to system infrastructure, to improve recommendation performance.
• Collaborate: Work with cross-functional teams to devise product strategies and develop intelligent solutions that support TikTok’s growth in key global markets.

The Must-Haves
• Background: Currently pursuing a Master’s degree in computer science, machine learning, or similar related fields. Candidates should possess good knowledge of theoretical and empirical research methods for addressing complex research problems.
• Experience: Familiarity with deep neural network architectures is required. The ability to commit to working for 12 weeks during Summer 2027 is essential.
• Skills: Solid knowledge and hands-on experience with at least one popular deep learning framework, such as PyTorch or TensorFlow, are mandatory. Proficiency in C/C++, Python, and shell programming languages is expected, coupled with a deep understanding of data structures and algorithm design.
• Bonus: Research experience in one or more areas including applied machine learning, machine learning infrastructure, large-scale recommendation systems, or market-facing machine learning products. Strong first-author publications in top AI conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) are highly valued, as is previous internship experience in an AI research organization.