TikTok Shop engineering team is looking to solve the problem of supporting the implementation of supply chain and logistics algorithm capabilities, and developing high concurrent online services and CV/LLM projects.
Requirements
- Familiar with mainstream KV (Redis/MongoDB), ElasticSearch and vector retrieval architecture, familiar with common basic components such as message queue and rule engine, familiar with Big data computing tools such as Hive Hdfs Hbase, with multi-threading and high-performance design, coding and performance Experience in tuning.
- Understanding of machine learning principles, understand the workflow of algorithm engineers, and have experience in model engineering tuning is preferred;
- 0-3 years minimum experience developing highly scalable backend services and systems using at least one of Java/Golang/Python.
- Experience with Java/Golang/Python
- Familiarity with Big data computing tools such as Hive Hdfs Hbase
- Experience with multi-threading and high-performance design
- Experience with mainstream KV (Redis/MongoDB), ElasticSearch and vector retrieval architecture
Responsibilities
- Responsible for TikTok Shop Logistics algorithm online services, data processing link infrastructure work;
- Provide high-performance, high-availability and flexible architecture design;
- Solve engineering problems in a complex ecosystem, ensure stability of services, and continuously improve R&D efficiency;
Other
- Bachelor or higher degree in Computer Science or related technical discipline
- Hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department
- Excellent problem disassembly and analysis skills, cross-team communication and coordination skills are preferred
- Day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits
- 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)
