Platform Intelligence Intern

ZooxFoster City, CA
Onsite

About The Position

Zoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a driverless future. Our mission is to make transportation safer, more sustainable, and accessible to everyone. At Zoox, innovation, collaboration, and a bold vision for the future drive everything we do. Zoox’s internship program offers hands-on experience with cutting-edge technology, mentorship from some of the industry’s brightest minds, and the opportunity to make meaningful contributions to real projects. We seek interns who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox’s mission. Zoox is looking for a Platform Intelligence Intern to design and ship production-ready AI products for our internal platform. Today, internal users navigate multiple systems and disconnected data sources to answer everyday questions about operations, performance, and reliability. Your mission is to collapse that friction into a single, intelligent experience — one that surfaces the right metrics, predicts issues before they escalate, and answers questions in natural language. This is a hands-on, build-focused internship with definitive deliverables and measurable impact on how Zoox teams work every day. You will own end-to-end delivery of three connected products on the internal Zoox platform: Analytics Layer — a unified analytics surface that consolidates fragmented metrics across internal systems into a single, trustworthy view, eliminating data inconsistencies and reducing the need to query multiple tools. Predictability Engine — ML-driven forecasting and anomaly detection on key operational metrics, giving teams early warning on trends, regressions, and capacity needs before they become incidents. Internal Chatbot — a conversational AI assistant that lets users ask questions in plain English and instantly get the metrics, dashboards, and answers they need — a true one-stop shop for internal queries and analytics.

Requirements

  • Currently pursuing a degree in Computer Science, Machine Learning, Data Science, or a related field
  • Good academic standing
  • Able to commit to a 12-week internship during the following summer 2026 cohort: June 15th - September 4th
  • Ability to relocate to the Bay Area, CA for the duration of the internship
  • Interns at Zoox may not use any proprietary information they are working on as part of their thesis, any published work with their university, or to be distributed to anyone outside of Zoox
  • Strong programming skills in Python; comfort with SQL and at least one cloud data stack
  • Practical experience with LLM APIs, RAG pipelines, embeddings, or fine-tuning
  • Foundation in ML/statistics: regression, classification, time-series forecasting, evaluation methodology
  • Bias for shipping — you measure success by what users actually use, not by what you build

Nice To Haves

  • Experience building chatbots, agents, or natural-language-to-SQL systems
  • Familiarity with data platforms (Snowflake, Databricks, BigQuery) and BI tools (Tableau, Looker)
  • Background in MLOps, model monitoring, or production ML deployment
  • Prior internship or project work delivered to real users

Responsibilities

  • Partner with platform, data, and operations teams to scope user pain points and translate them into AI product requirements
  • Design, prototype, and ship working features within the 12-week window — not research artifacts, but tools real users adopt
  • Build retrieval, ranking, and LLM-powered query interfaces that connect to existing internal data sources
  • Develop predictive models (time-series, classification) for key business and operational metrics
  • Instrument usage, measure adoption, and iterate based on real user feedback
  • Document architecture, runbooks, and handoff materials so the work scales beyond your internship

Benefits

  • medical insurance
  • housing stipend (relocation assistance will be offered based on eligibility)
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