Job Description

As a Forward Deployed Engineer at RLWRLD, you'll own the complete deployment lifecycle of our robotics systems, from data collection and model fine-tuning through production troubleshooting and observability. You'll work directly with customers in the field, rapidly diagnosing and fixing hardware, software, and perception failures while collecting operational insights that feed back into our core AI models. You'll be one of the first hires on the US team and work directly with partners like NVIDIA and AWS.

What You'll Do

• Drive end-to-end deployment cycles: data collection, model fine-tuning, physical system setup, and production monitoring.
• Isolate and patch hardware, software, and perception failures quickly under dynamic demo and production conditions.
• Gather raw operational data and failure modes from deployed systems to inform foundation model training and architecture.
• Troubleshoot complex integrations across perception hardware, compute stacks, and edge deployment environments.
• Travel 50–75% to customer sites across the US, adapting to unpredictable field deployment schedules.

What We're Looking For

• 2–8 years deploying robotics or automation solutions in factory, warehouse or logistics environments.
• Early-stage startup mindset: hands-on, proactive, comfortable debugging hardware and software integrations in the field.
• Practical debugging experience with perception hardware (optical cameras, depth sensors, tactile sensors).
• Basic understanding of and some exposure to Vision-Language-Action (VLA) models; academic or lab work counts.
• Eager to dive deep and learn, genuinely enthusiastic about physical AI and robotics.
• Willing to travel extensively and to be in the SF office ~3 days a week.

Nice to Have

• Hands-on experience with GPU compute stacks and edge deployment environments.
• Korean language proficiency (helpful for working with the Seoul team, not required).

Compensation

• $180,000–$220,000 base, early-stage equity grant, premium medical, dental and vision.

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