Machine Learning Scientist Intern (TikTok - Content Ecology - LLM application) - 2027 Start (PhD)
About the team
The Content Ecology team builds next-generation AI products and scalable platform capabilities that power how content is created, understood, discovered, and governed across TikTok globally. Leveraging cutting-edge technologies such as LLMs/MLLMs, multimodal learning, and Agentic AI, the team addresses complex, high-impact challenges across Local Services, Search, Short Drama, Creator Assistance, and AIGC. By uniting frontier AI research with product innovation, our team drives scalable solutions that elevate experiences for users, creators, and merchants worldwide.
PhD internships provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Responsibilities
- Develop and optimize LLM/MLLM, Agent, NLP, CV, and recommendation models to improve TikTok’s content ecosystem.
- Design, build, and optimize advanced Agentic AI frameworks, focusing on core components like planning, tool use, skills, and memory.
- Implement multimodal AI solutions, integrating video, text, and speech understanding.
- Train and fine-tune deep learning models using TensorFlow, 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.
Qualifications
Minimum Qualifications
- PhD in Computer Science, Machine Learning, AI, or a related field.
- Able to commit to working for 12 weeks during the Summer of 2027.
- Strong programming skills in Python, C++, or similar languages.
- Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
- Solid understanding of machine learning fundamentals and the modern AI stack.
- Strong proficiency in integrating AI tools into knowledge discovery and research workflows.
Preferred Qualifications
- Experience with distributed computing and optimizing AI models for real-world applications.
- Ability to apply machine learning techniques to enhance business and user experiences.
- Deep knowledge of agent architectures, including planning, tool use (e.g., LangChain, LlamaIndex), skills, and memory systems.
- Publications in top AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.) or strong contributions to open-source AI projects.
- Excellent communication skills to collaborate across teams.
Benefits
- Day one access to health insurance, life insurance, and wellbeing benefits.
- 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half).
- Eligibility for housing allowance if not working 100% remote.
Pay
The hourly rate for this position is $60.