Human-Centered AI Research Intern: Causal LLM Reasoning

Tri; Los Altos (CA); Hybrid; USD 62,000 - 90,000; Part time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Paid Time Off

Job summary

Toyota Research Institute (TRI) invites a highly motivated PhD research intern to join the Adaptive Behavior Systems team within Human-Centered AI Division. You will explore causal reasoning in language models, collaborating with ML researchers and social scientists to test and improve methods and prepare publications.

The role emphasizes ownership from inception to validation, cross-functional collaboration, and strategy discussions on business impact at TRI.

Qualifications

• PhD student in AI/ML, computer science, data science, statistics or related field.
• Publication record or demonstrated research in causal inference.
• Hands-on experience with LLM evaluation/benchmarking, mechanistic interpretability, prompting and prompt optimization.
• Experience with Python and DL frameworks like PyTorch.
• Interest in human-centered research including qualitative/quantitative methods.
• Excellent communication and teamwork skills.

Responsibilities

• Perform research and publish in a relevant venue; target NeurIPS, ICML, ICLR, and more.
• Take ownership of the project from inception to validation of methods.
• Collaborate cross-functionally with researchers across fields to leverage generative AI for understanding human behavior.

Skills

Python programming

DL frameworks

Excellent communication

Teamwork

Human-centered research interest

Education

PhD student in AI/ML/CS/DS/Statistics

Tools

PyTorch

Job description

Toyota Research Institute (TRI) invites a highly motivated PhD research intern to join the Adaptive Behavior Systems team within Human-Centered AI Division. You will explore causal reasoning in language models, collaborating with ML researchers and social scientists to test and improve methods and prepare publications.

The role emphasizes ownership from inception to validation, cross-functional collaboration, and strategy discussions on business impact at TRI.