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Sigma · 17 hours ago

AI/ML Graduate Engineering Intern (Summer 2026)

San Francisco, CA

Internship

Onsite

Intern

$70/hr - $90/hr

Start in 2026 Spring

Sigma is a cloud analytics and business intelligence tool that empowers business teams to explore data effortlessly. As an AI/ML Graduate Engineering Intern, you will work alongside the AI/ML team to identify and support high-impact AI opportunities, contribute to AI infrastructure development, and tackle innovative UX problems.

AnalyticsBusiness IntelligenceCloud Data ServicesComputerSoftware

Comp. & Benefits

No H1B

Responsibilities

Work alongside and learn from our growing AI/ML team

Partner with product, design, and engineering teams to identify high-impact AI/ML opportunities and support the usage of AI in our product and internal development processes

Prototype and productionize AI systems that feel intuitive but do a lot under the hood—recommendations, natural language interfaces, agentic workflows, and more

Contribute to the development of an AI/ML infrastructure that powers both internal tooling and customer-facing features

Tackle novel UX problems at the intersection of AI, BI, and apps

Qualification

Machine LearningDeep LearningApplied AIProduction-grade AI/ML systemsML lifecycleCloud InfrastructureBuilding AI systemsFast-moving startup experience

Required

Applicants must be currently enrolled in a university graduate degree program in the U.S with a graduation date of December 2026 or later

Able to intern in person in our San Francisco office from May/June 2026 through August or early September 2026

You must be legally authorized to work in the US during the Summer 2026 program

Current Graduate student studying AI/ML or CS with a focus in AI at a U.S. accredited university

Solid knowledge of machine learning, deep learning, and applied AI

Baseline understanding of building and deploying production-grade AI/ML systems

Knowledge of the full ML lifecycle: data curation, training, deployment, monitoring

A track record of building —whether it's recommendations, search, machine translation, or something equally complex that demonstrates your domain knowledge