ML Engineer - Ads Ranking & Video Semantics

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 317,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) match

Paid parental leave

Wellbeing benefits

Paid holidays

Paid sick days

Personal time off

Job summary

TikTok Inc. is hiring for an engineering role focused on building and optimizing the complete advertising ranking pipeline.

You will develop retrieval, coarse and fine ranking models and apply cutting-edge deep learning and recommendation techniques to improve ad relevance across a vast video platform. The role involves designing scalable back-end systems, indexing millions of videos, and deploying robust pipelines to process large-scale data daily.

Qualifications

• BS degree in Computer Science, Computer Engineering or a related field.
• Proficient in programming languages including Go, C/C++, Python.
• Experience with machine learning, data mining, data analysis and distribution systems.
• Strong problem solving, critical thinking and clear communication.
• Experience with ML, DL, NLP, ranking/recommendation systems, backend and large-scale systems.
• Good product sense and ability to design and implement features.

Responsibilities

• Develop and optimize the advertising ranking funnel from retrieval to fine-ranking models.
• Apply state-of-the-art DL and recommendation algorithms to improve ad relevance.
• Build large-scale video content indexing and retrieval to support vector-level matching across millions of videos.
• Set up content understanding pipelines for multiple business scenarios processing tens of millions of videos daily.
• Apply Embedding Distillation and Hard Negative Mining to optimize training.

Skills

Go

C/C++

Python

Machine Learning

Data Mining

Data Analysis

Distributed Systems

Back-end Systems

Education

BS in Computer Science / Computer Engineering

Job description

TikTok Inc. is hiring for an engineering role focused on building and optimizing the complete advertising ranking pipeline.

You will develop retrieval, coarse and fine ranking models and apply cutting-edge deep learning and recommendation techniques to improve ad relevance across a vast video platform. The role involves designing scalable back-end systems, indexing millions of videos, and deploying robust pipelines to process large-scale data daily.