AI Builder Intern
Scale AI - San Francisco, CA; New York, NY
Posted Jun 6, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- $74K-$112K From the posting source checked Jun 20, 2026
- 401(k) match
- Not verified
Was this benefit information wrong? Tell us.
Market context
- U.S. role benchmark (BLS OEWS)
- $61,842 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +1.9% - Slower
50% above the BLS role benchmark for operations aggregate.
Matched to SOC 11-1021 - Operations aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
- Equity
- Offered From the posting source checked Jun 20, 2026
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
AI Builder Intern San Francisco, CA; New York, NY ABOUT THE ROLE This isn't a research internship. You won't spend the summer writing reports or sitting in strategy meetings. You'll spend it building - shipping AI-powered tools, automating workflows, and deploying agentic systems that real teams at Scale AI use every day. Embedded in the Data & Technology org, you'll work directly alongside engineers, data scientists, and ops leads on live automation initiatives. If you have strong instincts for what AI can do today, a bias for building over theorizing, and a fluency in modern LLM tooling - this role is for you. ──────────────────────────────────────── WHAT YOU'LL BUILD Agentic Workflows & Automation → Design and deploy multi-step agentic workflows using LLM-integrated frameworks (LangChain, LangGraph, CrewAI, or similar) → Build API-connected automations that tie together internal tools - Slack, Salesforce, Notion, and internal data systems → Prototype and iterate fast; build things that work, then make them better AI Tooling & Internal Products → Develop lightweight internal tools and dashboards that surface AI outputs to business teams → Vibe-code functional UIs - React, plain JS, or whatever gets to working fastest - for internal adoption → Identify friction points in current workflows and propose AI-first replacements Measurement & Signal → Instrument your own work - capture usage signals, time-saved estimates, and adoption metrics from day one → Contribute to the org's ROI measurement framework by tagging your projects to defined value categories ──────────────────────────────────────── A NOTE ON "VIBE CODING" We're not precious about
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