Accelerated Science Intern, Representation Learning for Molecules and Materials

Location: Los Altos, California, United States; hybrid, in-office role

Salary: $45–$65/hour for California-based roles

Company

hirify.global develops AI, robotics, driving, and materials science technologies to improve human mobility and quality of life.

What you will do

• Implement and evaluate algorithms for learning and coordination among agents with different data and computational capabilities.
• Prototype information-sharing, predictive-model updating, and computational task-selection methods.
• Design controlled benchmarks comparing coordinated, independent-agent, and centralized approaches.
• Evaluate model accuracy, communication costs, and computational efficiency through reproducible experiments.
• Contribute documented code and help translate research into internal reports, publications, and patent disclosures where appropriate.

Requirements

• Currently enrolled in a doctoral program in computer science, machine learning, statistics, applied mathematics, electrical engineering, or a related discipline.
• Strong foundations in machine learning, probability, and optimization, with demonstrated experience implementing and evaluating algorithms.
• Familiarity with multi-agent systems, distributed or federated learning, or information theory.
• Proficiency in Python and modern machine-learning tooling, including tools such as PyTorch, experiment tracking, and reproducibility practices.
• Ability to collaborate across disciplines and translate research ideas into working code.

Nice to have

• Experience with distributed computing.

Culture & Benefits

• Paid 12-week summer internship with hybrid, in-office work.
• Collaboration with universities, national laboratories, and colleagues across global Toyota.
• Medical, dental, and vision insurance.
• Paid time off, including holiday pay and sick time.
• Diverse, inclusive, innovative, and collaborative work environment.