ByteDance
Research Scientist - Model Capability Boundary Exploration and AI Data Flywheel System Development - Global Frontier Tech Recruitment Program - 2027 Start (PhD)
San Jose, California · Full-time · Posted Oct 28, 2026
- Education
- Currently pursuing or recently completed a Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field.
About the job
Develops a real-world AI data flywheel to turn platform logs, cases, feedback, and environmental information into structured insights for improving foundation models and business-system agents.
What you'll do
- Build a model-as-a-service platform for LLM-based applications.
- Develop and maintain platform capabilities for training, fine-tuning, inference, model management, and resource orchestration.
- Manage GPU resources and provide computing capacity efficiently.
What they ask for
- Currently pursuing or recently completed a Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related technical field.
- Research experience in at least one of: LLM post-training and alignment, model evaluation, test-time scaling, agent systems, or large-scale data curation and optimization.
- Demonstrated research ability through publications, substantial research projects, or internships.
- Ability to work independently on open-ended research problems, from problem formulation through experimental execution.
Nice to have
- Interest in foundation models and data-centric AI, including data flywheels, continual learning, data curation and valuation, or algorithm-infrastructure co-design.
- Multiple first-author publications, or relevant internship/research experience, especially with scalable ML systems and real-world deployment.
Tools
LLM, GPU
AI focus
Build an AI data flywheel from real-world usage data and feedback to improve foundation models and agent systems, including their tools, memory, workflows, and environment.
Model-written summary · the original posting is authoritative