The role
From TikTok's own posting.
Team Introduction
Our mission in experimentation and evaluation team is to build the next-gen A/B testing platform, that empowers the company to make data-driven decision for the products. The supported scenarios include recommendation, push, ads, search, mobile app, UI interaction and service upgrades etc.
Our platform's capabilities cover the entire experiment life cycle, from experiment design, experiment creation, metrics calculation, statistical analysis to final evaluation and launch. In the process of rapid iteration, we provide reliable services for businesses to make bold hypotheses and cautious verification.
As a software engineer in experimentation and evaluation team, you will have the opportunity to build, optimize and grow one of the largest data platforms in the world. Your work will have a direct and huge impact on the company's core products as well as hundreds of millions of users.
- Design and build efficient, reliable data transformations for reporting, growth analysis, and multi-dimensional analytics
- Design and implement scalable, robust, and extensible big data systems that support core products and experimentation use cases
- Build and evolve platform services covering the full A/B testing lifecycle: experiment design, metrics computation, statistical analysis, evaluation, and launch decisions
- Apply strong engineering practices and system design principles to create maintainable, high-quality systems used by both engineers and non-technical users
- Collaborate closely with product managers, data scientists, and partner teams to translate business problems into technical solutions
- Explore and integrate LLM-based capabilities to improve platform intelligence, usability, and developer/product workflows
Minimum Qualifications
- BS or MS degree in Computer Science or a related technical field, or equivalent practical experience
- Strong back-end engineering skills
- Experience with big data technologies such as Hadoop, MapReduce, Hive, Spark, Metastore, Presto, Flume, Kafka, ClickHouse, or Flink
- Experience with data analysis, data ingestion, and data integration
- Solid communication and collaboration skills
Preferred Qualifications
- Industry experience building large-scale distributed systems in a production environment
- Experience with ETL pipelines, data system architecture, schema design, and data modeling
- Experience with front-end development and/or distributed big data systems (strong plus)
- Experience in data privacy and security–related projects
- Hands-on experience or strong interest in LLMs, including applying them to real product or platform use cases
- Strong statistical foundations and familiarity with experimentation or A/B testing concepts