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Part-Time Student Worker AI & Automation Supply Chain, Quality & Reliability
Job Location:
Job Location:
Foster, CA - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
28 May 2026 (30+ days ago)
Posted:
Application Deadline:
15 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
The Supply Chain Quality & Reliability (SCQR) organization at Zoox builds and manages the external ecosystem and internal safeguards that allow Zoox to build and operate. We secure the third-party technologies goods and services Zoox depends on; define how Zoox engages with its global supplier and vendor base; embed reliability into the vehicle from early concept through long-term fleet operations; steward the Zoox Quality Policy and culture from the smallest supplier part to the rider experience; guarantee the health of the physical infrastructure that supports our fleet at scale; drive Zooxs sustainability strategy toward our Amazon Climate Pledge Net Zero 2040 commitment; manage third-party risk and supplier resilience; and safeguard Zooxs reputation through ethical compliant and strategic commercial engagement with the outside world. As Zoox scales toward commercial deployment the volume and complexity of supplier quality reliability infrastructure and procurement data are growing rapidly across all of these areas and we are investing in AI to help our team work smarter faster and more proactively across the full SCQR mandate.
Zoox is launching a dedicated AI & Automation initiative within SCQR made up of 3-4 co-op interns working together as a centralized team that partners with our SCQR leaders and their teams to identify build and deploy AI-driven solutions across the organization. The AI & Automation Co-op Intern will join this pod and contribute to one of the most exciting AI adoption initiatives at Zoox building agentic systems RAG pipelines and MCP integrations against real SCQR data and coaching the SCQR team to extend and maintain these capabilities long after the co-op term ends. The pod reports directly into SCQR leadership to ensure strategic focus executive visibility and access across the broader management team.
In This Role You Will
- Partner with SCQR leaders and team members workflows and identify high-leverage opportunities where AI can eliminate toil accelerate decisions and surface insights the team would otherwise miss
- Design and build AI agents RAG pipelines and MCP server integrations that work against Zooxs real SCQR data supplier scorecards non-conformance reports audit findings CAPA responses inspection records reliability signals infrastructure readiness data contracts and procurement transactions
- Ship production-ready tools that the SCQR team will actually adopt and use in their daily work not proofs of concept that die in a notebook
- Run hands-on coaching sessions office hours and documentation efforts so SCQR team members can extend maintain and build on what youve shipped after your co-op term ends
- Develop reusable components patterns and playbooks so that each interns work compounds across the pod and across future co-op cohorts
- Present progress measured impact and forward priorities to SCQR leadership on a regular cadence
Qualifications
- Currently pursuing a Bachelors or Masters degree in Computer Science Computer Engineering Electrical Engineering Machine Learning or a related discipline and enrolled in a co-op program
- Able to commit to a minimum of a 12-week co-op term
- Demonstrated hands-on experience building agentic AI systems: function calling tool use multi-step planning and orchestration
- Hands-on experience with at least two of the following: Retrieval-Augmented Generation (RAG) (vector stores retrieval strategies evaluation) fine-tuning (LoRA SFT or similar) Model Context Protocol (MCP) server development prompt engineering at production scale
- Fluency in Python and direct experience working with at least one LLM provider API (Anthropic OpenAI or similar)
- Strong written and verbal communication skills with the ability to explain technical work clearly to non-technical engineering operations and quality stakeholders
- A portfolio or write-up of at least one agentic system you have built end-to-end open source prior internship or personal project all welcome
Bonus Qualifications
- Prior exposure to manufacturing supply chain supplier quality procurement reliability engineering or quality management systems
- Experience shipping AI-powered tools that were used by real people beyond yourself (open source projects with users internal tools at prior internships side projects with adoption)
- Experience with LLM evaluations observability guardrails or safety tooling
- Familiarity with enterprise data platforms (e.g. Snowflake Databricks) business systems (e.g. SAP Oracle) or quality management systems
- Experience working in a cross-functional environment partnering with non-technical teams
Program Requirements
- Currently pursuing a B.S. or M.S. in a relevant engineering field
- Available for a 6 month project
- Able to commit to at least 20 hours per week
- Ability to commute on-site to one of our offices
- Student Worker may not use proprietary Zoox information in university theses publications or share it outside
$30 per hour.
This is a contract position and employment for this position will be through a vendor contracted with Zoox. The hourly pay range is posted and you will be eligible for a benefits package as offered by the vendor.
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
About Company
We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable for everyone. This is on-demand autonomous ride-hailing.
