Algorithm Engineer - TikTok Location Based Services (Singapore)

Responsibilities

TikTok 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.

• 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.

Minimum Qualifications:

• 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.


• Experience in IP, base station, WiFi network location optimization, with deep understanding of systematic construction and optimization of location capabilities domestically or overseas.

Preferred Qualifications:

• Good communication and requirement understanding skills to efficiently collaborate with PMs for project iteration.


• Strong sense of ownership, good learning ability, and capability to grow rapidly with the team.


• Experience in overseas location and spatiotemporal data mining is preferred.