Senior Backend Software Engineer (Location-Based Services) - TikTok Local Service
May 12, 2025 Singapore
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 5,001 - 10,000 employees
- Industry: Entertainment & Gaming
Responsibilities
The TikTok LBS Platform aims to build a high-quality global LBS database and high-performance location-based services that connect TikTok users with nearby merchants and local services.
- Build fused geolocation capabilities by integrating multiple signal sources, such as IP, Wi-Fi, and GPS, to support TikTok Local Services and other TikTok products.
- Build Nearby and Location Profile Services to support TikTok Local Services and other location-based experiences.
You'll explore cutting-edge technologies alongside experts, pushing the boundaries of what's possible. Every line of code you write will serve billions of users. We are a professional and driven team with a collaborative, open, and low-hierarchy culture where people can work together in an equal and relaxed environment.
Responsibilities
- Participate in building an online streaming data scheduling system to ensure high performance, scalability, and reliability of data scheduling.
- Participate in building the end-to-end geolocation data access pipeline, including online and offline data cleansing modules, as well as the development, microservice encapsulation, deployment, and integration of algorithmic models.
- Develop and optimize core geolocation microservices, including online storage, geolocation inference, and location fusion services, to support high-QPS requests from multiple upstream services.
- Continuously analyze and identify system bottlenecks and areas for improvement, driving enhancements in system performance, scalability, and stability.
- Design, build, and evaluate LLM-powered workflows, including prompt engineering, Retrieval-Augmented Generation (RAG), tool use, and agent orchestration, to improve the efficiency of feature engineering and accelerate the development and iteration of geolocation microservices.
- Collaborate with AI engineers to establish efficient module update, deployment, and release mechanisms and processes, improving overall system development and iteration efficiency.
Qualifications
Minimum Qualifications:
- Bachelor's degree or higher in Computer Science or a related field.
- Familiarity with at least one programming language such as Java, Golang, PHP, Python, or C++, with a preference for experience in Golang or Java.
- Knowledge including but not limited to Linux systems and principles, MySQL, NoSQL, RPC, MQ, caching technologies, and microservices architecture.
- Experience with building high-concurrency services.
Preferred Qualifications:
- Strong coding and technical documentation skills, with a strong attention to code quality and style. Familiarity with fundamental design patterns and software engineering principles, with the ability to continuously monitor and optimize systems and coordinate across teams to drive project implementation.
- Understanding of geolocation big data processing workflows, with practical experience in areas such as microservice encapsulation, and the development and deployment of algorithmic models. Prior experience in geolocation big data processing and data management is preferred.
The TikTok LBS Platform aims to build a high-quality global LBS database and high-performance location-based services that connect TikTok users with nearby merchants and local services.
- Build fused geolocation capabilities by integrating multiple signal sources, such as IP, Wi-Fi, and GPS, to support TikTok Local Services and other TikTok products.
- Build Nearby and Location Profile Services to support TikTok Local Services and other location-based experiences.
You'll explore cutting-edge technologies alongside experts, pushing the boundaries of what's possible. Every line of code you write will serve billions of users. We are a professional and driven team with a collaborative, open, and low-hierarchy culture where people can work together in an equal and relaxed environment.
Responsibilities
- Participate in building an online streaming data scheduling system to ensure high performance, scalability, and reliability of data scheduling.
- Participate in building the end-to-end geolocation data access pipeline, including online and offline data cleansing modules, as well as the development, microservice encapsulation, deployment, and integration of algorithmic models.
- Develop and optimize core geolocation microservices, including online storage, geolocation inference, and location fusion services, to support high-QPS requests from multiple upstream services.
- Continuously analyze and identify system bottlenecks and areas for improvement, driving enhancements in system performance, scalability, and stability.
- Design, build, and evaluate LLM-powered workflows, including prompt engineering, Retrieval-Augmented Generation (RAG), tool use, and agent orchestration, to improve the efficiency of feature engineering and accelerate the development and iteration of geolocation microservices.
- Collaborate with AI engineers to establish efficient module update, deployment, and release mechanisms and processes, improving overall system development and iteration efficiency.
Minimum Qualifications:
- Bachelor's degree or higher in Computer Science or a related field.
- Familiarity with at least one programming language such as Java, Golang, PHP, Python, or C++, with a preference for experience in Golang or Java.
- Knowledge including but not limited to Linux systems and principles, MySQL, NoSQL, RPC, MQ, caching technologies, and microservices architecture.
- Experience with building high-concurrency services.
Preferred Qualifications:
- Strong coding and technical documentation skills, with a strong attention to code quality and style. Familiarity with fundamental design patterns and software engineering principles, with the ability to continuously monitor and optimize systems and coordinate across teams to drive project implementation.
- Understanding of geolocation big data processing workflows, with practical experience in areas such as microservice encapsulation, and the development and deployment of algorithmic models. Prior experience in geolocation big data processing and data management is preferred.
The TikTok LBS Platform aims to build a high-quality global LBS database and high-performance location-based services that connect TikTok users with nearby merchants and local services.
- Build fused geolocation capabilities by integrating multiple signal sources, such as IP, Wi-Fi, and GPS, to support TikTok Local Services and other TikTok products.
- Build Nearby and Location Profile Services to support TikTok Local Services and other location-based experiences.
You'll explore cutting-edge technologies alongside experts, pushing the boundaries of what's possible. Every line of code you write will serve billions of users. We are a professional and driven team with a collaborative, open, and low-hierarchy culture where people can work together in an equal and relaxed environment.
Responsibilities
- Participate in building an online streaming data scheduling system to ensure high performance, scalability, and reliability of data scheduling.
- Participate in building the end-to-end geolocation data access pipeline, including online and offline data cleansing modules, as well as the development, microservice encapsulation, deployment, and integration of algorithmic models.
- Develop and optimize core geolocation microservices, including online storage, geolocation inference, and location fusion services, to support high-QPS requests from multiple upstream services.
- Continuously analyze and identify system bottlenecks and areas for improvement, driving enhancements in system performance, scalability, and stability.
- Design, build, and evaluate LLM-powered workflows, including prompt engineering, Retrieval-Augmented Generation (RAG), tool use, and agent orchestration, to improve the efficiency of feature engineering and accelerate the development and iteration of geolocation microservices.
- Collaborate with AI engineers to establish efficient module update, deployment, and release mechanisms and processes, improving overall system development and iteration efficiency.
Qualifications
Minimum Qualifications:
- Bachelor's degree or higher in Computer Science or a related field.
- Familiarity with at least one programming language such as Java, Golang, PHP, Python, or C++, with a preference for experience in Golang or Java.
- Knowledge including but not limited to Linux systems and principles, MySQL, NoSQL, RPC, MQ, caching technologies, and microservices architecture.
- Experience with building high-concurrency services.
Preferred Qualifications:
- Strong coding and technical documentation skills, with a strong attention to code quality and style. Familiarity with fundamental design patterns and software engineering principles, with the ability to continuously monitor and optimize systems and coordinate across teams to drive project implementation.
- Understanding of geolocation big data processing workflows, with practical experience in areas such as microservice encapsulation, and the development and deployment of algorithmic models. Prior experience in geolocation big data processing and data management is preferred.
Responsibilities
ResponsibilitiesThe TikTok LBS Platform aims to build a high-quality global LBS database and high-performance location-based services that connect TikTok users with nearby merchants and local services.
- Build fused geolocation capabilities by integrating multiple signal sources, such as IP, Wi-Fi, and GPS, to support TikTok Local Services and other TikTok products.
- Build Nearby and Location Profile Services to support TikTok Local Services and other location-based experiences.
You'll explore cutting-edge technologies alongside experts, pushing the boundaries of what's possible. Every line of code you write will serve billions of users. We are a professional and driven team with a collaborative, open, and low-hierarchy culture where people can work together in an equal and relaxed environment.
Responsibilities
- Participate in building an online streaming data scheduling system to ensure high performance, scalability, and reliability of data scheduling.
- Participate in building the end-to-end geolocation data access pipeline, including online and offline data cleansing modules, as well as the development, microservice encapsulation, deployment, and integration of algorithmic models.
- Develop and optimize core geolocation microservices, including online storage, geolocation inference, and location fusion services, to support high-QPS requests from multiple upstream services.
- Continuously analyze and identify system bottlenecks and areas for improvement, driving enhancements in system performance, scalability, and stability.
- Design, build, and evaluate LLM-powered workflows, including prompt engineering, Retrieval-Augmented Generation (RAG), tool use, and agent orchestration, to improve the efficiency of feature engineering and accelerate the development and iteration of geolocation microservices.
- Collaborate with AI engineers to establish efficient module update, deployment, and release mechanisms and processes, improving overall system development and iteration efficiency.
Qualifications
QualificationsMinimum Qualifications:
- Bachelor's degree or higher in Computer Science or a related field.
- Familiarity with at least one programming language such as Java, Golang, PHP, Python, or C++, with a preference for experience in Golang or Java.
- Knowledge including but not limited to Linux systems and principles, MySQL, NoSQL, RPC, MQ, caching technologies, and microservices architecture.
- Experience with building high-concurrency services.
Preferred Qualifications:
- Strong coding and technical documentation skills, with a strong attention to code quality and style. Familiarity with fundamental design patterns and software engineering principles, with the ability to continuously monitor and optimize systems and coordinate across teams to drive project implementation.
- Understanding of geolocation big data processing workflows, with practical experience in areas such as microservice encapsulation, and the development and deployment of algorithmic models. Prior experience in geolocation big data processing and data management is preferred.
Additional Information
- Posted: May 12, 2025