Machine Learning Engineer Graduate (MultiMedia - Causal Inference) - 2025 Start (PhD)
San Jose, California, United States
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TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, 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.
About the Team:
The Multimedia Arch team is responsible for user experience optimization and cost optimization for the whole video on demand and live streaming system. We are building intelligence and personalized end-to-end multimedia systems to power the whole Tiktok ecosystem.
We are currently seeking a passionate machine learning engineer to join our team. In this role, you will collaborate with the product and engineering teams to identify opportunities and improve overall system performance and efficiency by integrating AI algorithms across the entire multimedia system. Your responsibilities will include designing service-side ML systems, implementing ML models, and validating their impact on the overall system through A/B testing.
We are looking for talented individuals to join our team in 2025. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2025.
Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Online Assessment
Candidates who pass resume evaluation will be invited to participate in TikTok's technical online assessment in HackerRank.
Responsibilities
- Apply causal inference algorithms to understand users and improve user experience at Tiktok.
- Develop machine learning solutions for user behavior prediction, app traffic prediction, and video understanding.
- Work cross-functionally with product managers, data scientists, and product engineers to understand insights, formulate problems, design and refine machine learning algorithms, and further drive the exciting growth of global TikTok users.
- Run regular A/B tests, perform analysis, and iterate algorithms accordingly.
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.
About the Team:
The Multimedia Arch team is responsible for user experience optimization and cost optimization for the whole video on demand and live streaming system. We are building intelligence and personalized end-to-end multimedia systems to power the whole Tiktok ecosystem.
We are currently seeking a passionate machine learning engineer to join our team. In this role, you will collaborate with the product and engineering teams to identify opportunities and improve overall system performance and efficiency by integrating AI algorithms across the entire multimedia system. Your responsibilities will include designing service-side ML systems, implementing ML models, and validating their impact on the overall system through A/B testing.
We are looking for talented individuals to join our team in 2025. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2025.
Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Online Assessment
Candidates who pass resume evaluation will be invited to participate in TikTok's technical online assessment in HackerRank.
Responsibilities
- Apply causal inference algorithms to understand users and improve user experience at Tiktok.
- Develop machine learning solutions for user behavior prediction, app traffic prediction, and video understanding.
- Work cross-functionally with product managers, data scientists, and product engineers to understand insights, formulate problems, design and refine machine learning algorithms, and further drive the exciting growth of global TikTok users.
- Run regular A/B tests, perform analysis, and iterate algorithms accordingly.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Engineering Jobs
Machine Learning Jobs
Tags: A/B testing Causal inference Engineering Machine Learning ML models PhD Streaming Testing
Perks/benefits: Career development
Region:
North America
Country:
United States
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