Machine Learning Engineer Graduate (TikTok Content Ecology) - 2027 Start (PhD)
About the Team
The Content Ecology team develops AI-powered products and platform capabilities that enhance how content is created, understood, discovered, and governed across TikTok. Leveraging cutting-edge technologies such as large language models (LLMs), multimodal learning, and agentic AI, the team addresses complex challenges across Local Services, Search, intelligent customer service, creator understanding, and AI-assisted content creation. By combining business-focused product innovation with scalable AI platform development, the team delivers impactful solutions that improve experiences for users, creators, and merchants while advancing frontier AI capabilities at global scale.
Responsibilities
- Architect and build standardized, configurable, and reusable pipelines for the entire lifecycle of models and agents—from data processing and training to deployment, monitoring, and governance.
- Partner with algorithm teams to understand their needs and provide a world-class infrastructure platform that accelerates their research and development cycles.
- Build robust observability and evaluation frameworks to ensure the reproducibility, reliability, and cost-efficiency of AI workloads at scale.
- Design and implement core platform infrastructure, including model/agent registries, feature stores, and high-throughput retrieval/RAG systems.
- Design, build, and optimize advanced Agentic AI systems, focusing on core components like planning, tool use, and memory.
Qualifications
Minimum Qualifications:
- Individuals who are completing or have recently completed a PhD degree in computer science, computer engineering, electrical engineering, applied mathematics, or a related discipline.
- Experienced in programming and algorithmic skills, proficient in languages such as Python or C++.
- Deep understanding of one of the following areas: NLP (Natural Language Processing), CV (Computer Vision), LLM (Large Language Models)/MLLM (Multimodal Language Models), Search, or Agentic AI.
- Experienced in one or more of the following topics: TensorFlow, PyTorch, or other machine learning frameworks.
- Good team communication and collaboration skills.
Preferred Qualifications:
- Experience in building ML model development for large-scale consumer-facing applications.
- Experience or domain expertise in one or more of the following areas is preferred: NLP, CV, LLM/MLLM, Agentic LLMs, Dialog Systems, Search, Recommendation Systems, or Creator Modeling.
- Published papers or hands-on project experience in the fields of NLP, CV, agent-based systems, or multimodal technologies.
Pay
The base salary range for this position is $128,000 - $316,800 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work; this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
Benefits
- Day one access to medical, dental, and vision insurance.
- 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).