Machine Learning Engineer , TikTok Engineering (Singapore) - 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 products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, 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 users we serve. Join us.

TikTok Engineering are building up an engineering team for core TikTok product in Singapore, to ensure TikTok continues a healthy growth, deliver the best product experience to all of our users, build the most attractive features to help users enjoy their time on TikTok, earn trust in privacy protection, and more.

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.

Job Responsibilities:
- Build machine learning solutions for TikTok products/platforms.
- Build industry leading recommendation system; develop highly scalable classifiers and tools leveraging machine learning;
- Understand product objectives and machine learning techniques; improve model and recommendation strategy;
- Understand user behavior and apply ML algorithms to optimize content consumption and production experience;
- Work with cross functional teams to grow company's product in important regional markets.

Qualifications

Minimum Qualifications
- Final year or recent graduate with a background in computer science, computer engineering, information systems or a related technical discipline from a university
- Solid engineering skills. Proficiency in at least two of: Linux, Hadoop, Hive, Spark, Storm.
- Strong machine learning background. Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning.
- Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, data-driven manner. High autonomy.

Preferred Qualifications
- Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product.
- Strong publications record in top conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, etc) and journals (e.g., TPAMI, JMLR)
- Track record of high impact research

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.

For TikTok
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.

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