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Research Intern: Meta-Cognitive Agentic AI Systems

Honda Research Institute USA
San Jose, CA

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Job Details

Internship

Qualifications

AI models
Research
AI platforms (beyond public GPTs)
Computational framework
Machine intelligence
Neural networks
Machine learning (ML) fundamentals
Machine learning frameworks

Full Job Description

Job Number: P25INT-49

Honda Research Institute USA (HRI-US) is seeking a self-motivated research intern to join our Cooperative Cognition Team in advancing the next generation of adaptive AI systems that can thrive in complex, human-AI collaborative environments. As an intern, you will help design and implement AI agents with metacognitive capabilities, focusing on areas such as multi-agent systems for long-horizon tasks, test-time scaling, and rapid adaptation to individual preferences. This work will contribute to developing robust, self-adapting and self-correcting AI partners that can quickly learn new tasks, adjust to dynamic teams, and cooperate effectively with humans. This includes exploring how internal model representations—such as hidden states, neural activations, and latent structures—can be analyzed and leveraged for self-monitoring, uncertainty estimation, and adaptive control in meta-cognitive agent architectures.

San Jose, CA

Key Responsibilities

Contribute to the development of metacognitive algorithms (assessment and intervention strategies) that enhance the efficiency, adaptability, and reliability of agentic AI systems.
Develop methods to analyze, probe, and manipulate neural activations and internal representations of foundation models (e.g., hidden states and latent features), including activation-level and circuit-level analysis, to enable meta-cognitive capabilities such as self-assessment, uncertainty awareness, and adaptive intervention.
Test-time scaling of multimodal (vision–language–action) models.
Improve the robustness and generalization of LLMs in long-horizon, multi-agent tasks.
Design and curate a benchmark suite for evaluating multimodal agentic systems in collaborative settings.

Minimum Qualifications

Currently enrolled as a Ph.D. student in Computer Science, Machine Learning, or a related field at a reputed university (exceptional M.S. candidates with a minimum of 1 year of research experience may also be considered.
Strong familiarity with agentic AI systems, modern foundation models, and their internal representations (e.g., hidden states, neural activations, embeddings, and latent structures).
Experience in open-source deep learning frameworks.

Bonus Qualifications

Experience with representation learning, mechanistic interpretability, or analysis of neural activations in foundation models.

Years of Work Experience Required

Desired Start Date

8/31/2026

Internship Duration

3 Months

Position Keywords

Agentic AI, Meta-Cognitive AI

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