Graduate ML Engineer, Recommender Systems (E-commerce)

TikTok; San Jose (CA); On-site; USD 150,000 - 317,000; Full time

Job summary

TikTok is seeking a highly capable engineer to advance our Global E-Commerce Content Recommendation systems. You will own end-to-end models for TikTok Shop, covering retrieval, ranking, multi-queue blending, and experimentation at scale.

You will work on multimodal representations, large-scale data processing, and online/offline evaluation to optimize for engagement and GMV, with a focus on fast, robust, and fair recommendations at scale.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics or related field.
• Strong algorithms and data-structures fundamentals with clean, efficient code.
• Solid foundations in machine learning, probability, and statistics with explanation of model behavior.

Responsibilities

• Own the end-to-end recommendation models for TikTok Shop across retrieval, ranking, and multi-queue blending.
• Iterate architectures for multi-task objectives including click, conversion, and GMV.
• Model user interest with long sequences and latency considerations.
• Develop multimodal representations combining images, text, and video with behavioral data.
• Design cold-start and content ecosystem mechanisms for new products and creators.

Skills

Algorithms & data-structures

ML foundations

Python

C++

Linux

Communication & collaboration

Education

Bachelor's degree in CS/EE/Math/Stats

Tools

PyTorch

TensorFlow

Spark

Flink

SQL

Python

C++

Linux

Job description

TikTok is seeking a highly capable engineer to advance our Global E-Commerce Content Recommendation systems. You will own end-to-end models for TikTok Shop, covering retrieval, ranking, multi-queue blending, and experimentation at scale.

You will work on multimodal representations, large-scale data processing, and online/offline evaluation to optimize for engagement and GMV, with a focus on fast, robust, and fair recommendations at scale.