Graduate ML Engineer, Trust & Safety – Seattle

TikTok; Seattle (WA); On-site; USD 122,000 - 243,000; Full time

Job summary

TikTok is seeking a Machine Learning Engineer Graduate for Trust & Safety in Seattle, starting in 2027. You will tackle state-of-the-art computer vision, NLP, and multimodal models to safeguard the platform, with onboarding by year-end and opportunities to grow through cross-functional collaboration.

The role emphasizes collaboration with product, engineering, and data science teams to deploy scalable ML solutions and tackle challenging content understanding tasks, including LLMs and

Qualifications

• Bachelor's or Master's degree in computer science or a related discipline.
• Hands‑on or academic experience in ML, LLMs, Recommendation Systems, and related areas.
• Strong coding skills.
• Curiosity towards new technologies and entrepreneurship, good communication and teamwork skills.

Responsibilities

• Collaborate with product teams to define business objectives and improve trust and safety strategy.
• Collaborate with engineering teams to deploy ML models, design online model workflow, and implement serving pipelines at scale.
• Collaborate with data scientists to understand key challenges and propose data-driven strategies.
• Work on state-of-the-art content understanding techniques including unimodal/multimodal content classifiers, learning models, RL models, and Large Language Models.

Skills

Machine learning

Large Language Models

Recommendation Systems

Strong coding skills

Teamwork and communication

Curiosity about new technologies

Education

Bachelor's or Master's degree in computer science

Job description

TikTok is seeking a Machine Learning Engineer Graduate for Trust & Safety in Seattle, starting in 2027. You will tackle state-of-the-art computer vision, NLP, and multimodal models to safeguard the platform, with onboarding by year-end and opportunities to grow through cross-functional collaboration.

The role emphasizes collaboration with product, engineering, and data science teams to deploy scalable ML solutions and tackle challenging content understanding tasks, including LLMs and