Machine Learning Engineer, Generative E-Commerce Recs

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

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) with company match

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Paid holidays

Paid sick days

Paid Personal Time

Job summary

TikTok Inc. is seeking researchers/engineers to build and scale a billion-user recommender system for global e-commerce content, including advanced retrieval, ranking, and generative components. You will explore world-class techniques, push hardware-optimized inference, and contribute to long-term research goals.

The role emphasizes publishing internal papers, patents, or presenting at top venues, while delivering production-ready systems and improvements to user experience and GMV.

Qualifications

• PhD in CS, AI, math, statistics or related field.
• Strong ML fundamentals and clean, efficient code.
• Experience in LLMs / foundation models, NLP, CV, RL, or recommendation / search / ads.
• Genuine enthusiasm for production-ready frontier methods.
• Strong problem-definition and decomposition skills.

Responsibilities

• Build and rewrite an industrial recommender system for a billion-scale user base.
• Scale models to trillions of parameters and optimize latency budgets.
• Develop end-to-end retrieval, ranking and blending with generative retrieval.
• Pursue original research via internal papers, patents, or external publications.

Skills

ML fundamentals

LLMs / foundation models

Algorithmic thinking

NLP / CV / RL

Clean, reproducible code

Education

PhD in CS/AI/Math/Stats

Tools

CUDA

Triton

Distributed training

Job description

TikTok Inc. is seeking researchers/engineers to build and scale a billion-user recommender system for global e-commerce content, including advanced retrieval, ranking, and generative components. You will explore world-class techniques, push hardware-optimized inference, and contribute to long-term research goals.

The role emphasizes publishing internal papers, patents, or presenting at top venues, while delivering production-ready systems and improvements to user experience and GMV.