Tech Lead: Multimodal ML & LLM Systems

TikTok; San Jose, Northern (CA, KY); Hybrid; USD 254,000 - 588,000; Full time

Benefits offered by this job

Healthcare benefits

401(k) with match

Parental leave

Disability coverage

Life insurance

Wellbeing program

Holidays

Sick days

Personal time off

Job summary

TikTok in San Jose is seeking a Tech Lead ML Engineer for Multimodal/LLM in Trust and Safety. You will own design and delivery of core ML modules, lead a small team of ML engineers, and shape end-to-end pipelines across data processing, training, evaluation, deployment, and monitoring.

The ideal candidate has a PhD/MS and 4+ years of hands-on ML experience, with production-ready model deployment and strong CV/NLP/LLM expertise.

Qualifications

• Master’s or Ph.D. in Computer Science, ML, AI or related field.
• 4+ years of hands-on ML system development experience.
• Experience leading small technical teams or driving major ML modules end-to-end.
• Production deployment of large-scale ML models.

Responsibilities

• Own the design and delivery of a core system module within a key content safety vertical.
• Lead ML engineers to deliver production-ready solutions with technical rigor.
• Architect and implement end-to-end ML pipelines: data processing, training, evaluation, deployment, monitoring.
• Apply advanced CV/NLP/LLM techniques to solve moderation challenges across video, image, text, and audio.
• Improve model performance via data analysis, error diagnosis, feature engineering, and model innovation.
• Collaborate with product, policy, operations to align technical solutions with safety requirements.

Skills

ML leadership

Production ML

CV/NLP/LLM

Model training/ eval/ tuning

data processing

ownership mindset

Architectural design

Deployment to production

Education

Master’s/PhD in CS/ML

Job description

TikTok in San Jose is seeking a Tech Lead ML Engineer for Multimodal/LLM in Trust and Safety. You will own design and delivery of core ML modules, lead a small team of ML engineers, and shape end-to-end pipelines across data processing, training, evaluation, deployment, and monitoring.

The ideal candidate has a PhD/MS and 4+ years of hands-on ML experience, with production-ready model deployment and strong CV/NLP/LLM expertise.