PhD ML Engineer Intern - Ads Monetization & Targeting

TikTok Inc.

San Jose (CA)

On-site

USD 68,000 - 97,000

Part time

14 days+

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Benefits offered by this job

Health insurance
Life insurance
Wellbeing benefits
Paid holidays
Housing allowance

Job summary

TikTok is seeking PhD interns to contribute to its Global Monetization Product and Technology teams. You will participate in developing a large-scale Ads system and lead state-of-the-art applied ML projects, owning targeting components within the monetization ecosystem.

This internship blends hands-on learning with collaboration across product and business teams, offering exposure to real-world research, a dynamic campus environment, and comprehensive benefits.

Qualifications

  • Currently pursuing a PhD in Computer Science, Software Engineering, Computer Engineering, or a related technical discipline.
  • Experience in and good theoretical grounding in machine learning concepts and techniques.
  • Excellent programming, debugging, and optimization skills in one or more general purpose programming languages, including but not limited to: Go, C/C++, Python.
  • Experience in one or more of the following frameworks: Tensorflow/PyTorch/MXNet, etc

Responsibilities

  • Participate in the development of a large-scale Ads system.
  • Responsible for the development of state-of-the-art applied machine learning projects.
  • Own key targeting components or strategies in the TikTok ads monetization ecosystem.
  • Work with product and business teams on product vision.

Skills

Go
C/C++
Python
ML concepts
Debugging

Education

PhD in Computer Science/Software Engineering/Computer Engineering

Tools

TensorFlow
PyTorch
MXNet

Job description

TikTok is seeking PhD interns to contribute to its Global Monetization Product and Technology teams. You will participate in developing a large-scale Ads system and lead state-of-the-art applied ML projects, owning targeting components within the monetization ecosystem.

This internship blends hands-on learning with collaboration across product and business teams, offering exposure to real-world research, a dynamic campus environment, and comprehensive benefits.

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