ByteDance
Agent Evaluation & Evolution Machine Learning Engineer Intern (AML-Ark-US) - 2027 Summer
San Jose, California · Internship · Posted Oct 28, 2026
- Education
- Currently pursuing a Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
About the job
Designs evaluation systems and benchmarks for LLM-based agents, analyzes agent performance, and helps turn evaluation findings into production improvements.
What you'll do
- Design agent evaluation systems for task success, tool use, reasoning quality, and reliability; build benchmarks and automated judging pipelines.
- Analyze execution traces and user feedback to identify failure patterns and recommend system improvements.
- Work with research, platform, and product teams to bring evaluation methods into production.
What they ask for
- Currently pursuing a Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- Solid foundation in machine learning and deep learning.
- Hands-on experience with LLM-based systems through research, internships, or projects.
- Strong Python skills, experience with a mainstream ML or agent evaluation framework, and demonstrated research or engineering ability.
Nice to have
- Publications at top-tier ML/NLP venues, especially in agent learning, self-improving/self-evolving/RSI, or agent evaluation.
- Experience with evaluation methodology, LLM post-training, reasoning and planning, continual learning, feedback-driven optimization, or large-scale log and trace analysis.
Tools
Python
AI focus
Evaluates LLM-based agents, including task success, tool use, reasoning quality, and reliability; develops benchmarks and automated judging pipelines and uses feedback and traces to improve agent systems.
Model-written summary · the original posting is authoritative