Agent Evaluation Evolution Machine Learning Engineer Intern (AML-Ark-US) - 2027 Summer
Actively Hiring
Full-time $28k Posted 29 days ago
Responsibilities
- check_circle Design evaluation systems for LLM-based agents, covering task success, tool use, reasoning quality, and reliability.
- check_circle Build benchmarks and automated judging pipelines, combining rule-based checks, model-based judging, and human review, etc.
- check_circle Analyze agent execution traces and user feedback to identify failure patterns and turn them into concrete system improvements.
- check_circle Support the closed loop from experience to capability, and work with research, platform, and product teams to bring methods into production.
Basic qualifications
- Currently pursuing a Bachelor's/ Master'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 (e.g., agents, tool calling, retrieval, multi-agent systems) through research, internships, or projects.
- Strong Python skills and experience with a mainstream ML or agent evaluation framework.
- Demonstrated research or engineering ability through publications, substantial projects, internships, or open-source work.
Preferred qualifications
- Publications at top-tier ML/NLP venues (e.g., NeurIPS, ICML, ICLR, ACL etc.), especially in agent learning, self-improving/self-evolving/RSI, or agent evaluation.
- Experience with evaluation methodology: metric design, model-based judging, or annotation and statistical analysis, etc.
- Familiarity with LLM post-training, reasoning and planning methods, or continual learning.
- Experience with feedback-driven optimization loops, or with large-scale log and trace analysis.
- Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
- Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
- Exercising sound judgment.
Tags & Focus Areas
Internship Remote Machine Learning Generative Ai Ai
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