AI Accelerator Intern: Build Production-Ready AI Tools

The RealReal; San Francisco (CA); On-site; USD 76,000 - 83,000; Part time

Benefits offered by this job

Hourly pay

Job summary

The RealReal is seeking motivated students for a 10-week AI Intern Program. You will design, build, and deploy production-ready AI tools that address real business challenges and drive operational efficiency.

You’ll work across systems, partner with teams to scale AI usage, and develop long-term technical roadmaps for impact. Responsibilities include designing AI solutions, integrating capabilities, and enhancing data pipelines to support scalable model deployments.

Qualifications

• Solid understanding of machine learning fundamentals and neural networks.
• Ability to translate complex technical concepts for stakeholders.
• Interest in applying AI to solve real-world problems and improve operations.

Responsibilities

• Design, prototype, and deploy production-ready AI models and tools.
• Review and integrate AI capabilities across systems for performance and automation.
• Prepare data pipelines and structures to support robust model deployment.
• Advise cross-functional teams on AI tool usage and prompting best practices.
• Develop technical roadmaps to scale AI tools across operations.
• Demonstrate impact with measurable efficiency gains to executives.

Skills

AI/ML fundamentals

Communication

Generative AI architectures

Prototyping & APIs

Cloud basics

Data engineering

Prompt engineering

Education

Bachelor's/Master's/PhD student in CS or AI

Tools

Streamlit

FastAPI

Flask

Docker

Pinecone

Milvus

Job description

The RealReal is seeking motivated students for a 10-week AI Intern Program. You will design, build, and deploy production-ready AI tools that address real business challenges and drive operational efficiency.

You’ll work across systems, partner with teams to scale AI usage, and develop long-term technical roadmaps for impact. Responsibilities include designing AI solutions, integrating capabilities, and enhancing data pipelines to support scalable model deployments.