AI/ML PhD Intern — Build AI for Data Workflows

Sigma; San Francisco (CA); On-site; USD 110,000 - 124,000; Full time

Benefits offered by this job

Equity

Generous health benefits

Flexible time off

Paid bonding time for all new parents

Traditional and Roth 401k

Commuter and FSA benefits

Lunch Program

Dog friendly office

Job summary

Sigma is seeking an AI/ML PhD Intern to contribute to the AI foundation powering Sigma’s data platform. You will work on research areas like search, recommendations, NLP, and agentic workflows, while helping build production-ready AI systems that feel intuitive to users.

Ideal candidates are PhD students with deep ML knowledge, experience deploying AI at scale, and a passion for turning research into impactful production solutions.

Qualifications

• Current PhD student in AI/ML at a U.S.-accredited university.
• Deep understanding of ML, deep learning, model architectures, optimization.
• Experience building and deploying production-grade AI/ML systems.
• Knowledge of data curation, training, deployment, monitoring across ML lifecycle.
• Ability to bridge research and application from concept to deployment.

Responsibilities

• Conduct original AI/ML research in search, recommendations, NLP, and agentic workflows.
• Prototype and productionize AI systems that feel intuitive yet operate deeply.
• Tackle UX challenges at the intersection of AI, analytics and data apps.
• Contribute to scalable AI/ML infrastructure for experimentation, training and evaluation of large models.

Skills

ML fundamentals

Deep learning

ML deployment

ML lifecycle

Research skills

Education

PhD in AI/ML

Tools

AWS

GCP

Azure

Job description

Sigma is seeking an AI/ML PhD Intern to contribute to the AI foundation powering Sigma’s data platform. You will work on research areas like search, recommendations, NLP, and agentic workflows, while helping build production-ready AI systems that feel intuitive to users.

Ideal candidates are PhD students with deep ML knowledge, experience deploying AI at scale, and a passion for turning research into impactful production solutions.