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# Forward Deployed Engineer

- **Company:** ONE STOP COLLECTIBLE CORP
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $180,000 - $220,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, System Configuration, Software Debugging, Operational Data Store, Systems Integration, Large Language Models, Hardware Debugging
- **Published:** November 6, 2026
- **Apply:** https://startup.jobs/forward-deployed-engineer-clera-10688577

## About the Role

* Two to eight years of hands-on experience deploying robotics or automation systems in factory, warehouse, or logistics settings.
 * Experience in forward deployed engineering, field engineering, ML or AI operations, robotics deployment, or customer-facing technical work.
 * Practical debugging experience with perception hardware such as optical cameras, depth sensors, tactile sensors, or pressure sensors.
 * Some exposure to Vision-Language-Action models or learned robot policies; academic or lab experience is relevant.
 * Comfort debugging hardware and software integrations, collecting data, and owning production fixes in a fast-moving environment.
 * Experience with GPU compute stacks and edge deployment is useful. Korean language proficiency is also helpful.
 * Willingness to travel 50% to 75% and work from the San Francisco office about three days per week.
 * Must have US work authorization or be eligible for an H-1B transfer. New visa sponsorship is not available.

## Description

Join a physical AI and robotics team deploying robotics systems in customer facilities. You will own deployments from data collection and model tuning through production troubleshooting, helping operational insights improve the underlying models., * Drive deployment cycles, including data collection, model fine-tuning, physical system setup, and production monitoring.

 * Diagnose and patch hardware, software, and perception failures in field and production environments.
 * Collect operational data and failure modes to inform foundation model training and architecture.
 * Troubleshoot integrations across perception hardware, compute stacks, and edge deployment environments.
 * Travel to customer sites across the United States, adapting to changing deployment schedules.