Research Engineer: Scalable ML for Moderation

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

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) matching

Parental leave

Disability insurance

Life insurance

Wellbeing benefits

Paid holidays

Paid sick days

Paid personal time

Job summary

TikTok is seeking strong machine learning researchers to build a next-generation content understanding system for monetization. You will grow business understanding, build scalable models, and partner with global teams to deliver reliable performance.

In this role you will develop an end-to-end moderation system with interpretable reasoning and automated decisions, collaborating across disciplines, with emphasis on production-ready ML and real-world impact.

Qualifications

• PhD in CS/EE/Math or related field, expected graduation within 12 months.
• Experience implementing, training, or deploying models in Ads, Search, Recommender Systems, NLP, CV, Multimodal, or Agent technologies.
• Proficient in Python and at least one DL framework (PyTorch or TensorFlow).

Responsibilities

• Build a leading moderation system enabling end-to-end rejection decisions, interpretable reasoning, and automated remediation.
• Ensure production-ready ML with scalable latency and reliability.
• Collaborate across disciplines with global teams to advance content understanding for monetization.

Skills

PhD in CS/EE/Math

Python

PyTorch

TensorFlow

NLP/Multimodal

Education

PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

Job description

TikTok is seeking strong machine learning researchers to build a next-generation content understanding system for monetization. You will grow business understanding, build scalable models, and partner with global teams to deliver reliable performance.

In this role you will develop an end-to-end moderation system with interpretable reasoning and automated decisions, collaborating across disciplines, with emphasis on production-ready ML and real-world impact.