Duration: 10 weeks (full-time), June through Early August.
Competitive Compensation: Tailored to your experience and skill set.
Format: Hybrid (4+ days in person) - Based in Palo Alto, CA off University Ave
Cohort Size: Small and mentorship-focused
Learning Goals: Develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.
Role Details
Interns will contribute to real data innovation projects involving
Data analysis and machine learning pipelines
AI agents, retrieval systems, and evaluation frameworks
Enterprise AI integration and deployment tooling
Product prototyping and applied research
Automation systems for large-scale organizational use
Real world enterprise use cases of graph theory
Gain direct exposure to Fortune 500 clients
Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.
Projects are oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.
Mentorship & Learning
Interns will work closely with experienced staff and technical mentors with expertise in:
Computer Science
Data Science & Analytics
Applied AI & Machine Learning
Enterprise Infrastructure
Scalable AI Deployment
Risk and Compliance Frameworks
Tax and Audit
The program is structured as a high-engagement cohort-based apprenticeship experience emphasizing:
Daily in person technical collaboration
Rapid learning and iteration
Exposure to real deployment challenges
Cross-disciplinary problem solving
Professional development in AI engineering and enterprise systems
Who Should Apply
We welcome applications from
Graduate students with a record of excellence
Exceptional advanced undergraduates
All candidates are required to be recommended by an accredited professor leading a relevant program at a top university. Will be verified during application process.
Strong candidates typically demonstrate
Programming experience
Curiosity about AI systems and emerging technologies
Initiative, creativity, and strong problem-solving ability
Prior technical, research, or project experience
You do not need deep expertise in every area, we value intellectual curiosity, adaptability, and motivation to build.