Operations Engineer Intern

Location:
 On-site (Bay Area)

Schedule:
 5 days/week

Compensation:
 Unpaid (Conversion opportunities available)

Commitment:
 Part-time or full-time

About the Role

We're looking for a highly organized Operations Intern who can work on-site every day and support a broad mix of responsibilities across device operations, customer onboarding, technical support, QA testing, and basic AI model maintenance. This role is great for someone close to graduation or recently graduated who enjoys hands-on work, problem-solving, and learning how hardware, software, and AI come together in a real product.

You'll support engineering, operations, customer success, and AI/ML teams by helping test devices, triage issues, prepare customer deployments, troubleshoot problems, and assist with small automation/scripting tasks.

What You'll DoCustomer Onboarding & Support

• Prepare devices and configurations for new deployments.
• Support customer onboarding workflows and setup verification.
• Provide first-line technical assistance on device or dashboard issues.
• Gather logs, screenshots, error details, and clear descriptions for engineering triage.
• Track customer tickets and update issue status in JIRA or internal tools.

Technical Issue Triage & Debugging

• Reproduce customer issues on-site to isolate root causes.
• Perform basic debugging: connectivity checks, firmware validation, cabling, sensor tests.
• Distinguish between hardware, software, workflow, and user-driven issues.
• Escalate well-documented findings to engineering.

Operations & Lab Support

• Assist with hardware assembly, alignment, wiring checks, and device configuration.
• Validate sensors, cameras, tablets, and mechanical components.
• Maintain an organized lab with labeled parts and standardized workflows.
• Track inventory of devices, replacement parts, and tools.
• Help prepare shipments (deployments or RMAs).

QA & Testing

• Run structured test cases for dashboard, mobile app, and tablet UI.
• Execute regression tests before releases.
• Document bugs with reproducible steps, screenshots/videos, and logs.
• Verify new features and user flows across hardware + software.

AI Model Support & Automation

• Assist with maintaining datasets used for AI model training.
• Help label, clean, and organize data for retraining cycles.
• Run simple scripts to trigger retraining, batch processing, or data exports.
• Verify model outputs against expected results and flag anomalies.
• Support automation tasks (e.g., Python scripts, small workflows, log parsers).
• Collaborate with AI/ML engineers on routine model evaluation tasks.

What We're Looking For

• On-site
  Monday–Friday; part-time or full-time hours supported (required).
• Extremely 
  organized
   with strong attention to detail.
• Comfortable working hands-on with hardware, sensors, cameras, and tools.
• Basic understanding of mobile apps, web apps, and technical troubleshooting.
• Strong communication skills for reporting issues clearly and professionally.
• Interest in AI/ML workflows, data pipelines, or automation.
• Preferred:
   Students close to graduation or recent graduates.

Bonus Experience:

• Python or scripting familiarity
• AI/ML coursework or personal projects
• Hardware/IoT testing
• JIRA, GitHub, Confluence, or ticketing tools
• Customer support or helpdesk experience

What You'll Learn

• How customer onboarding and support work in an AI-driven hardware/software product.
• How to triage and debug real hardware + software issues.
• How QA integrates into release cycles and product development.
• How AI models are maintained, evaluated, retrained, and automated in production.
• How cross-functional teams (Engineering, Ops, AI/ML, and CS) work together.
• How to work efficiently in a fast-paced startup environment.

Why This Role Matters

You'll be a critical part of making sure devices work smoothly, customers get a great experience, and AI models continue to improve over time. Your work directly impacts product quality, deployments, and our ability to scale.

Perks

• Hands-on experience across Operations, QA, Customer Support, and AI/ML workflows.
• Direct mentorship from engineering and operations leaders.
• Exposure to real AI-driven IoT systems.
• Strong experience for future roles in Ops, QA, AI, or Technical Support.