Applied Scientist Intern (Recommendation AI Lab) - 2026 Start (PhD)

Position Overview Global Monetization Product and Technology team are building the next-generation monetization platforms to help millions of customers grow their businesses, utilizing our products like TikTok. Our team develops a wide variety of advertisements for numerous uses including feeds, live streaming, branding, measurement, targeting, search, vertical solutions, creative solutions, and business integrity. Responsibilities Topic Content: This topic dives deep into TikTok's core global advertising scenarios, driving innovation and implementation of cutting‑edge generative technologies in search, recommendation, and advertising. By deeply integrating foundation models with the advertising business, we address key technical challenges in Large Recommender Models and Large Language Models (LLMs) to build a next‑generation intelligent advertising engine with autonomous decision‑making capabilities. We are looking for talented individuals to join us for an internship in 2026. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands‑on learning, enriching community‑building and development events, and collaboration with industry experts. Explore scaling laws for foundation models in recommendation and advertising, and build a foundation model based on unified multimodal semantic modeling. Build an intelligent ad placement system optimized for users' Long‑Term Value (LTV) and long‑term ROAS, achieving an optimal balance between commercial value and user experience. Optimize the full‑process training and online inference framework for foundation models, balance computing power costs and real‑time response performance, and resolve the performance‑latency trade‑off in real‑world deployment. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date). Qualifications Currently pursuing a PhD in Computer Science, Computer Engineering, or a related technical discipline. Modeling experience in one or more of the areas: Ads, Search engine, Recommender System, NLP/CV. Have a solid foundation in algorithms related to LLMs, including but not limited to comprehensive learning and practical experience in areas such as single‑modal LLM application and deployment. Preferred Qualifications Priority will be given to candidates with research results and extensive practical relevant fields, such as outstanding performance in natural language processing, computer vision, data modeling, or algorithm optimization, etc. Excellent programming abilities with a strong command of data structures and fundamental algorithms. For traditional coding roles, proficiency in C/C++ is required; for intelligent coding roles, proficiency in Python is required. Strong publications record in top conferences (e.g., ICLR, NeurIPS, ICML, ACL, EMNLP, NACCL, CVPR, ICCV, and ECCV) is a plus. Benefits & Compensation Compensation Description (Hourly) - Campus Intern: $60 hourly. Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance. The Company reserves the right to modify or change these benefits programs at any time, with or without notice. Equal Opportunity & Legal Information For Los Angeles County (unincorporated) candidates: 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. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; Exercising sound judgment. All qualified applicants will receive concussion identical to non‑qualified applicants. The Company is an equal opportunity employer. #J-18808-Ljbffr Tik Tok