CV/NLP/Multimodal LLM Research Scientist Graduate (Trust and Safety) - 2026 Start (PhD)

CV/NLP/Multimodal LLM Research Scientist Graduate (Trust & Safety) - 2026 Start (PhD) Location: Seattle Employment Type: Regular Responsibilities Develop computer vision or multimodality models to recognize violating content on TikTok. Explore cutting‑edge multimodal or computer‑vision large models (e.g., CLIP, COCA, ALBEF, BLIP, Flamingo, ViT‑G, ViT‑22B, EVA‑enormous). Apply large language models to business scenarios such as pre‑training, zero‑shot/few‑shot learning, and hard‑case mining. Continuously optimize the distributed training framework for large‑model training. Qualifications Actively completing or recently completed a PhD. Research experience in computer vision, multimodality, or LLM. Proficiency with at least one deep‑learning framework (PyTorch, TensorFlow, etc.). Strong analytical, problem‑solving, logical thinking, communication, and collaboration skills. Preferred: Published papers at major AI conferences or journals (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, TPAMI, IJCV, etc.). Compensation & Benefits The base salary range for this position in Seattle is $148,200 – $300,960 annually. Base pay is one part of the total package and may be supplemented with discretionary bonuses/incentives and restricted stock units. Benefits include medical, dental, and vision insurance; a 401(k) savings plan with company match; paid parental leave; short‑term and long‑term disability coverage; life insurance; wellbeing benefits; 10 paid holidays per year; 10 paid sick days per year; and 17 days of paid personal time (prorated upon hire with increasing accruals by tenure). Equal Employment Opportunity Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Contact Information By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed at #J-18808-Ljbffr TikTok