Graduate ML Engineer - Build Scalable Recommender Systems

TikTok; San Jose (CA); On-site; USD 162,000 - 388,000; Full time

Job summary

TikTok is seeking a PhD‑level researcher/engineer to join the Global E‑Commerce Content Recommendation team in San Jose. You will build and rewrite an industrial recommender serving a billion‑scale user base across short-video, livestream, and product scenarios, delivering end-to-end retrieval, ranking, and blending with ultra-low latency.

The role emphasizes scaling models, generative retrieval, and injecting world knowledge, using CUDA/Triton kernels and distributed training.

Qualifications

• Individuals who are completing or have recently completed a PhD degree in Computer Science, AI, Mathematics, Statistics or a related discipline
• Solid ML and engineering fundamentals: you understand the math behind the models, and you write clean, efficient, reproducible code with a strong command of algorithms and data structures
• Deep research or engineering practice in at least one of: LLMs / foundation models, NLP, CV, RL, or recommendation / search / ads — and you can articulate why you made the choices you made, and where they fell short
• Genuine enthusiasm for LLM / LRM techniques: you want frontier methods live in production, not parked at offline metrics
• Strong problem definition and decomposition: faced with an ambiguous problem that has no standard answer, you find your own foothold

Responsibilities

• Build and rewrite an industrial recommendation system serving billions of users across short-video, livestream, and product scenarios.
• Scale models: push ranking models to billions of parameters while keeping millisecond latency.
• Develop one-stage generative retrieval and train autoregressive models.
• Inject world knowledge to mine latent user interests and semantic representations.
• Push training and inference to hardware limits with CUDA/Triton and distributed training.

Skills

PhD in CS/AI

ML fundamentals

LLM/NLP/RL research

Problem solving

Production mindset

Education

PhD in Computer Science or related field

Tools

CUDA

Triton

Job description

TikTok is seeking a PhD‑level researcher/engineer to join the Global E‑Commerce Content Recommendation team in San Jose. You will build and rewrite an industrial recommender serving a billion‑scale user base across short-video, livestream, and product scenarios, delivering end-to-end retrieval, ranking, and blending with ultra-low latency.

The role emphasizes scaling models, generative retrieval, and injecting world knowledge, using CUDA/Triton kernels and distributed training.