Machine Learning Engineer, Dedup (TikTok) - 2025 Start

Responsibilities

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
TikTok RecCore Dedup team conducts research and introduces cutting-edge AI technologies to our products. In order to provide the best user experience, we build large-scale systems and support various production strategies including video deduplication, originality recognition, copyright detection, content safety, and content moderation.

We are looking for talented individuals to join us 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.

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.

Responsibilities
- Build the Dedup and Copyright system, supports billions of users all over the world
- Based on the product requirements, develop models and systems to detect duplicated and similar materials among billions of videos
- Introduce new AI technologies to our online system and improve the performance
- Improve the reliability of the system, manage the challenges of scale and complexity
- Support the production of scalable and optimised AI/machine learning (ML) models
- Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models
- Run experiments to test the performance of deployed models, and identifies and resolves bugs that arise in the process
- Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm
- Work with the relevant software platforms in which the models are deployed

Qualifications

Minimum Qualification
- Final year or recent graduate with a background in computer science, computer engineering, information systems or other related discipline;
- Min 1 year of experience in Machine Learning, familiar with at least one DeepLearning framework, e.g. PyTorch, Tensorflow.
- Experienced in Multimedia or Computer Vision, e.g. Image/Video/Audio retrieval, Representation Learning, Re-Identification, Unsupervised/Self-supervised learning.

Preferred Qualifications:
- Have experience working in large scale tech companies.
- Master's or above degree in computer science or other relevant major.

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.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy.

If you have any questions, please reach out to us at [email protected]