[US] Forward Deployed Engineer

About RLWRLD

At RLWRLD, we are solving one of the most critical bottlenecks in robotic automation: true physical dexterity. Our state-of-the-art Robotics Foundation Models (RFMs) power autonomous systems capable of complex manipulation, consistently topping benchmarks like the RoboCasa Kitchen Leaderboard. We are one of the few RFM companies actively executing real-world deployments in customer facilities across Korea, Japan, and the US.

Work with a team that has deep expertise in Robotics, and AI. Founders are serial deep tech entrepreneurs, having exited previous deep tech start-ups to companies like Intel.

What You'll Do

• Own the Stack: Drive the entire deployment lifecycle, taking responsibility for data collection, model fine-tuning, physical system deployment, troubleshooting, and production observability and fixes.
• Solve Field Issues: Rapidly isolate and patch hardware, software, and perception failures under dynamic demo and production conditions.
• Bridge R&D and Ops: Collect raw operational data and failure modes from the field to directly inform our core foundational model training and architecture.

Qualifications

• Field Experience: 2-3+ years deploying robotics or automation solutions in factory or logistics settings.
• Scrappy Mindset: Early-stage startup experience with a hands-on, proactive approach to debugging complex hardware and software integrations.
• Perception Stack: Working knowledge and practical debugging experience with perception hardware (hi-fi optical cameras, depth perception sensors, pressure/tactile sensors).
• VLA Exposure: Basic modeling understanding and practical exposure to Vision-Language-Action (VLA) architectures (academic or lab experience is fully valid).
• Travel Flexibility: Willingness to travel 50%-75% to customer sites across the US and adapt to unpredictable field deployment hours.
• Korean Fluency: Functional or professional proficiency in Korean (required for 1-2 roles on this team to interface with international teams).

Nice-to-Haves & Language

• Compute Infrastructure: Hands-on experience with GPU compute stacks and edge deployment environments.

Compensation & Benefits

• Base Salary: $180,000 - $220,000 - commensurate with experience.
• Equity: Early-stage equity grant.
• Benefits: Premium medical, dental, and vision coverage included.