Job Description

Responsibilities

• Build and improve internal tools that accelerate developer productivity and system reliability.
• Design and prototype components of distributed training and data infrastructure.
• Contribute to automation, deployment, and observability systems across multi-cloud and on-premises environments.
• Collaborate with engineers and researchers to bring new ML infrastructure capabilities to production.
• Participate in code reviews and technical discussions while learning scalable infrastructure development practices.

Requirements

• Pursuing a BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field.
• Strong programming skills in Python, Go, or C++.
• Familiarity with Linux systems, Docker, Kubernetes, or similar technologies.
• Curiosity about cloud computing, including AWS, Azure, or GCP, and large-scale distributed systems.
• Interest in infrastructure supporting machine learning research and model deployment at scale.
• Collaborative, detail-oriented, and eager to take on complex technical problems.

Benefits

• Paid internship lasting three months sometime between May and August 2027.
• Based in San Mateo, California, with four days per week in the office.
• Relocation stipend and assistance for interns moving to the Bay Area.
• 100% covered medical, vision, and dental benefits.
• 401(k) plan with a 4% company match.
• Unlimited PTO.
• 12 weeks of paid parental leave plus six months of work-from-home flexibility.
• Annual $2,000 wellness stipend.
• Annual $1,000 learning and development stipend.
• Daily lunches and snacks provided in the office.

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