AI-Driven Risk & Integrity ML Engineer

TikTok USDS Joint Venture; Seattle (WA); On-site; USD 130,000 - 246,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Paid parental leave

Disability coverage

Life insurance

Wellbeing benefits

10 holidays per year

Job summary

TikTok USDS Joint Venture is seeking a PhD-level candidate to lead advanced risk and integrity architectures across a billion-user ecosystem. You will leverage transformer and graph neural networks on large-scale social-graph data, integrate Generative AI and multimodal technologies, and work within a security-focused, global team.

This in-person role emphasizes scalable, robust ML infrastructure. Applicants should have deep ML foundations, strong coding skills, and experience with PyTorch,

Qualifications

• PhD or recent-completion in Computer Science, Engineering, Math, or Statistics.
• Strong ML fundamentals; experience with transformer and graph neural networks on large-scale data.
• Programming proficiency in Python, C++, or Go; familiarity with distributed systems and DL frameworks.

Responsibilities

• Lead algorithmic architecture and governance for TikTok US across key risk domains.
• Build high-precision risk representation models using heterogeneous data.
• Research and counter global adversarial threats with self-evolving defense systems.
• Drive integration of Generative AI and multimodal tech into risk lifecycle.

Skills

Transformer architectures

GNN architectures

Python

C++

Go

PyTorch

Distributed computing

Education

PhD in CS/Engineering/Math/Statistics

Tools

Spark

Flink

PyTorch

Job description

TikTok USDS Joint Venture is seeking a PhD-level candidate to lead advanced risk and integrity architectures across a billion-user ecosystem. You will leverage transformer and graph neural networks on large-scale social-graph data, integrate Generative AI and multimodal technologies, and work within a security-focused, global team.

This in-person role emphasizes scalable, robust ML infrastructure. Applicants should have deep ML foundations, strong coding skills, and experience with PyTorch,