AI Platform Engineer Co-Op Intern

Location: Hybrid in the San Francisco Bay Area, United States

Company

hirify.global builds AI-native operating systems for large, regulated institutions, with production deployments across government, insurance, healthcare, and financial services.

What you will do

• Build and improve Kubernetes- and Terraform-based infrastructure across production and customer environments.
• Develop tooling and automation that makes infrastructure safer and easier to deploy and operate.
• Work with cloud infrastructure, networking, CI/CD, and containerized systems.
• Build observability capabilities including metrics, logging, tracing, dashboards, and monitoring.
• Investigate performance and reliability issues across distributed systems and AI workloads.
• Support infrastructure for AI inference, data pipelines, and large-scale backend services while participating in code reviews and architecture discussions.

Requirements

• Current undergraduate student at junior or senior level, pursuing Computer Science, Machine Learning, Data Science, or a related degree.
• Strong software engineering fundamentals gained through coursework, internships, research, or personal projects.
• Programming experience with Python, Go, Java, C++, or a similar language.
• Exposure to or interest in cloud infrastructure, distributed systems, operating systems, networking, or databases.
• Familiarity with or willingness to learn Kubernetes, Terraform, Docker, AWS, GCP, Azure, and observability tools.
• Interest in solving performance, reliability, and scalability problems with a proactive approach to learning.

Culture & Benefits

• Winter/Spring Co-Op runs from January 11, 2027 through April 30, 2027.
• Competitive co-op compensation.
• Hands-on mentorship from experienced AI engineers and researchers through code reviews, design discussions, and collaboration.
• Opportunity to work on real production systems used globally.
• Potential consideration for future internships or full-time roles.
• Daily lunches when working onsite.