Machine Learning Scientist Intern (-Content Ecology—LLM PhD
Listed on 2026-03-12
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Responsibilities
The Content Ecology Algorithm Team drives Tik Tok’s AI innovations in LLMs, NLP, Computer Vision (CV), multimodal learning, and recommendation algorithms. We develop cutting‑edge AI capabilities that power multiple business lines, including Local Services, Search, Core Video Architecture, Professional Content (PGC), and User Growth (UG).
Our Work Includes- Short Video Content Understanding – Building multimodal AI models to analyze video, text, and speech.
- Global Trending Event Detection – Developing real‑time AI systems to detect viral trends worldwide.
- Intelligent Customer Service – Implementing chatbot and automation solutions using LLMs.
- AI-Driven Content Discovery – Enhancing personalized content recommendations through advanced algorithms.
With millions of daily users, our work directly impacts Tik Tok’s growth and user engagement.
We are looking for talented individuals to join us for an internship in 2026. Internships at Tik Tok aim to offer students industry exposure and hands‑on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at Tik Tok.
PhD internships at Tik Tok 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.
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).
Responsibilities- Develop and optimize LLM, NLP, CV, and recommendation models to improve Tik Tok’s content ecosystem.
- Implement multimodal AI solutions, integrating video, text, and speech understanding.
- Optimize LLM‑powered search, discovery, and content recommendation systems for better user engagement.
- Train and fine‑tune deep learning models using Tensor Flow, PyTorch, or other ML frameworks.
- Deploy and scale machine learning solutions in a distributed computing environment.
- Work closely with AI researchers, software engineers, and business teams to apply AI technologies effectively.
Minimum Qualifications:
- PhD in Computer Science, Machine Learning, AI, or a related field.
- Strong programming skills in Python, C++, or similar languages.
- Hands‑on experience with deep learning frameworks such as Tensor Flow or PyTorch.
- Solid understanding of machine learning, NLP, CV, or recommendation algorithms.
- Experience with distributed computing and optimizing AI models for real‑world applications.
- Ability to apply machine learning techniques to enhance business and user experiences.
- Publications in top AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.) or strong contributions to open‑source AI projects.
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Job Information【For Pay Transparency】Compensation Description (Hourly) – Campus Intern
The hourly rate range for this position in the selected city is $60- $60.
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.
For Los Angeles County (unincorporated) CandidatesQualified 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…
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