Algorithm Engineer Graduate (TikTok LBS Singapore) - 2026 Start (BS/MS)

Responsibilities

TikTok Location Based Services (LBS) Platform's goal is to build a global high-quality LBS database and high-performance LBS services that connects TikTok users with nearby merchants and local services.
- Build a global POI (Point of Interest) database, multi source POI integration and POI nearby search service to support TikTok local services.
- Build geocoding database, geocoding service, and IP Location service to support TikTok local services and monetization product

Here, you'll be exploring cutting-edge technology alongside experts, pushing the boundaries of imagination. Here, every line of your code will serve billions of users. Here, the team is professional and driven, with a collaborative atmosphere that is equal and relaxed.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok.

Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.

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 location models based on multi-source data such as GPS, IP, base stations, and WiFi, optimize location strategies, and continuously improve location accuracy.
- Responsible for mining and tagging global user profiles to understand users' behaviors.
- Apply big location data to provide customized solutions with higher efficiency, better results, and lower costs for TikTok's commercialization, local services, e-commerce, and other businesses to continuously enhance industry competitiveness.

Qualifications

Minimum Qualifications
- Final year or recent graduate with a background in computer science, statistics, or other relevant, machine-learning-heavy majors.
- Strong programming skills, solid foundation in data structures and algorithms, and excellent system design capability.
- Solid knowledge of machine learning and deep learning theories, with hands-on experience and understanding of common problems and solutions in model iteration optimization.

Preferred Qualifications
- Good communication and requirement understanding skills to efficiently collaborate with PMs for project iteration.