Live E-Commerce ML Engineer: Generative Recs & LTV

TikTok; San Jose (CA); On-site; USD 128,000 - 317,000; Full time

Job summary

TikTok in San Jose seeks a candidate for the Global E-commerce Recommendation Live Algorithm team. You will work on the core recommendation stack for live commerce, covering recall to ranking, in a dynamic real-time environment.

You will build models, connect videos, streams, and products with user behavior, apply multimodal learning, and collaborate with cross-functional partners to ship scalable solutions that drive GMV and user engagement.

Qualifications

• Bachelor’s degree in CS/EE/Math/Stats or related field.
• Solid ML foundation in recommendations, search, ads, NLP, or related AI.
• Strong programming skills in Python or C++, with PyTorch experience.
• Knowledge of data structures, algorithms, and large-scale ML systems.
• Analytical, problem-solving, and ability to translate business problems into models.
• Self-driven, ownership of model iteration and online impact.

Responsibilities

• Build and optimize models across recall, pre-ranking, ranking, and mixed ranking to improve GMV and user value.
• Develop cross-domain, multimodal solutions linking videos, streams, products, and behavior.
• Advance next-gen recommender tech including generative methods and RL-based optimization.
• Collaborate with cross-functional teams to run experiments and measure business impact.

Skills

Python

C++

PyTorch

Machine learning fundamentals

Data structures & algorithms

Online/offline modeling

Education

Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics or related discipline

Tools

Python

PyTorch

C++

Job description

TikTok in San Jose seeks a candidate for the Global E-commerce Recommendation Live Algorithm team. You will work on the core recommendation stack for live commerce, covering recall to ranking, in a dynamic real-time environment.

You will build models, connect videos, streams, and products with user behavior, apply multimodal learning, and collaborate with cross-functional partners to ship scalable solutions that drive GMV and user engagement.