Machine Learning Engineer Graduate (Tech and Product, USDS) - 2027 Start

About the team

The Tech and Product team of TikTok USDS is missioned to empower TikTok US users to have a great user experience with strong data security and privacy protections, focusing on compliance, reliability, business and product support, and efficiency improvement.

As part of this team, you will build and scale high-impact Machine Learning solutions—including recommendation engines, search relevance, and e-commerce systems—designed specifically to deliver personalized, high-performing experiences while ensuring world-class data governance, privacy compliance, and system security for US users.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. 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 our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Depending on the team that you'll be considered for, you can expect to

• Design, build, train, and evaluate machine learning models for recommendation systems, search ranking, query understanding, or conversion prediction.
• Implement efficient pipelines for feature extraction, model training, evaluation, offline-to-online deployment, and A/B testing.
• Process and analyze massive user behavior data and catalog logs using distributed systems to construct real-time and offline features.
• Optimize online inference latency and system throughput for high-QPS production microservices.
• Conduct continuous A/B testing, analyze online metrics, identify bottleneck areas, and iterate on models to drive business goals.

Minimum Qualification(s)

• Individuals who are completing or have recently completed a Bachelor's/ Master's degree in Computer Science, Engineering, Math, Statistics, or a related discipline.
• Solid background in Data Structures, Algorithms, Computer Systems, and Software Design.
• Strong theoretical understanding and practical knowledge of machine learning concepts.

Preferred Qualification(s)

• Prior internship or project experience in Recommendation Systems, Search Engine, Computational Advertising, or E-Commerce AI
• Experience with distributed computing frameworks