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Senior Machine Learning Engineer, TikTok Ads Core- Business Account

Tik Tok

Company : Tik Tok

Location : San Jose, CA, 95113

Posted Date : 15 September 2025

Job Details

Responsibilities
TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.
Why Join Us
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.
TikTok is one of the fastest-growing apps globally, and personalized online advertising is a major revenue source for Internet companies nowadays. It is one of the most attractive fields in the Internet industry for top talents interested in solving exciting technical challenges.
We're looking for innovative Machine Learning Engineers to join our TikTok Ads Core team. Our team is a platform team that develops state-of-art ad technologies, including ranking, retrieval, targeting, bidding, auction, etc. You will be part of a team that's optimizing ads format and ranking strategies, and you will be responsible for bringing a better return on investment for advertisers.
What You'll Do
• Build highly scalable machine learning systems/models to improve ads ranking results.
• Explore, develop and experiment with new features to improve model accuracy.
• Understand ads platform objectives and take full advantage of modern machine learning to improve ad quality, relevancy, and select the best ad formats delivered to end-users.
• Develop robust core systems and algorithms, including ads format selection system, ads ranking system, model serving system, etc.
Qualifications
Minimum Qualifications:
• BS/MS degree in Computer Science, Computer Engineering, or a related technical discipline with 5+ years industry experience and 2+ year model optimization experience.
• Solid programming skills, proficient in C/C++ and Python. Familiar with basic data structure and algorithms. Familiar with Linux development environment.
• Good analytical thinking capability. Have essential knowledge and skills in statistics.
• Good theoretical grounding in deep learning concepts and techniques.
• Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet), familiar with its architecture and implementation mechanism.
Preferred Qualifications:
• Good understanding in one of the following domains: ads bidding & auction, ads quality control, and online advertising systems (familiar with one or more of these terms: CPC/CPM, CTR/CVR, Ranking /Targeting, Conversion/Budget, Campaign/Creative, Demand/Inventory, DSP/RTB).
• Experience in resource management and task scheduling with large scale distributed software (such as Spark and TensorFlow).
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at [redacted]

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