PhD Intern, Ads Machine Learning Data Platform – Ads Machine Learning Data Platform

Job Description

Research Engineer Intern (Ads ML Infra) | TikTok

The Tone:
This is an internship at TikTok, based at one of its global offices. TikTok is the leading destination for short-form mobile video, with a mission to inspire creativity and bring joy across the world. This Research Engineer Intern role is integral to the Ads machine learning data platform team, which is responsible for developing highly efficient and stable infrastructure for collecting and processing massive datasets. The work directly contributes to improving the quality of TikTok’s ads system through advanced machine learning for training, serving, and privacy enforcement.

The TL;DR
• Role: Research Engineer Intern (Ads ML Infra)
• Type: Internship
• Location: In-person, TikTok office (specific city not provided in listing)
• Pay: $60 hourly
• Team: Ads machine learning data platform team
• Mission: Lead projects to build and operate scalable and reliable Ads ranking infrastructure systems, contributing to the quality and efficiency of TikTok’s global ads system.
• Tech Stack:

What You’ll Actually Do
• Project Leadership: Lead projects focused on building and operating scalable and reliable Ads ranking infrastructure systems.
• Technical Guidance: Provide technical leadership and guidance to fellow team members and project peers.
• Cross-functional Communication: Communicate across various teams, organizations, and both internal and external stakeholders to drive engineering initiatives.
• Innovation: Spearhead innovation efforts by introducing new ideas and technologies to the team.

The Must-Haves
• Background: Currently pursuing a PhD in Computer Science or related technical disciplines, with a Bachelor’s degree as a minimum qualification.
• Experience: Demonstrated experience in managing projects.
• Skills: Strong Computer Science fundamentals including algorithms, data structures, and software design; proven problem-solving abilities; solid coding proficiency; and a good understanding of algorithms, particularly causal inference, uplift models, and deep learning.
• Bonus: Experience within the Ads domain; experience with building large-scale ranking infrastructure.