ML Engineer – Video Understanding & Core Feed Safety

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) with company match

Parental leave

Disability coverage

Paid time off

Job summary

TikTok Inc. is seeking a Dedup/ML Engineer in San Jose to build and scale systems for billions of users. You will design and deploy models for video understanding and content integrity, integrating AI tech to boost accuracy and efficiency.

You will develop scalable data pipelines, run production experiments, and collaborate with cross-functional teams for smooth ML deployment and monitoring.

Qualifications

• Bachelor's degree in Computer Science or related field
• At least 1 year of industry experience in Machine Learning
• Proficiency with PyTorch or TensorFlow
• Experience in Multimedia or Computer Vision areas such as image/video/audio retrieval, representation learning, re-identification, or unsupervised/self-supervised learning

Responsibilities

• Build and scale the Dedup and Copyright system that supports billions of users globally
• Design and deploy machine learning models to support video understanding and content integrity
• Integrate cutting-edge AI technologies to improve model accuracy, performance, and system efficiency
• Develop scalable data pipelines and infrastructure to support training and serving of ML models on real-time, unstructured data
• Run experiments to evaluate and debug models in production environments
• Collaborate with cross-functional teams to ensure smooth deployment and monitoring of ML systems

Skills

Machine Learning

Video understanding

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Job description

TikTok Inc. is seeking a Dedup/ML Engineer in San Jose to build and scale systems for billions of users. You will design and deploy models for video understanding and content integrity, integrating AI tech to boost accuracy and efficiency.

You will develop scalable data pipelines, run production experiments, and collaborate with cross-functional teams for smooth ML deployment and monitoring.