Hybrid Internship: Multi-Agent ML for Coordinated AI

Toyota Research Institute Inc.; Los Altos (CA); Ibrido; USD 62.000 - 90.000; Part-time

Vantaggi offerti da questo lavoro

Medical/dental/vision insurance

Paid time off

Hybrid in-office role

Internship program

Descrizione del lavoro

Toyota Research Institute (TRI) is seeking a research intern to develop algorithms and computational systems for multi-agent learning and coordination in a collaborative, cutting-edge environment. The role emphasizes distributed approaches, information-sharing, and benchmarking against centralized methods.

The internship is 12 weeks, hybrid in-office in California, with compensation at $45–$65 per hour. Applicants should be pursuing a PhD in a relevant field and able to contribute to

Competenze

• Enrolled in a doctoral program in CS/ML/Statistics/Applied Math/EE.
• Strong foundations in ML, probability, and optimization.
• Experience implementing and evaluating algorithms.
• Familiarity with multi-agent systems, distributed learning, or information theory.
• Proficiency in Python and ML tooling; distributed computing a plus.

Mansioni

• Implement and evaluate learning and coordination algorithms for agents.
• Prototype information-sharing and model-updating methods.
• Design benchmarks comparing coordination strategies.
• Evaluate model accuracy, costs, and efficiency with reproducible workflows.
• Contribute high-quality code and draft internal reports/publications.

Conoscenze

Python

PyTorch

Distributed computing

Multi-agent systems

Information theory

Experiment tracking

Research software development

Formazione

PhD candidate in CS/ML/Statistics/Applied Math/EE

Strumenti

PyTorch

Experiment tracking

Reproducible research

Descrizione del lavoro

Toyota Research Institute (TRI) is seeking a research intern to develop algorithms and computational systems for multi-agent learning and coordination in a collaborative, cutting-edge environment. The role emphasizes distributed approaches, information-sharing, and benchmarking against centralized methods.

The internship is 12 weeks, hybrid in-office in California, with compensation at $45–$65 per hour. Applicants should be pursuing a PhD in a relevant field and able to contribute to