Forward Deployed Engineer

Seoulstart; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

RLWRLD is seeking a Forward Deployed Engineer for our US office to own the full deployment lifecycle—from data collection and model fine-tuning to field deployment and production monitoring. You will diagnose and patch hardware, software, and perception issues under dynamic conditions, and feed ground-truth field data back into model training and system architecture.

The role bridges R&D and Operations, requiring hands-on field experience with robotics deployments and a track record of solving

Qualifications

• Field experience deploying robotics or related systems.

Responsibilities

• 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.

Skills

Field Experience

Job description

RLWRLD# Forward Deployed EngineerNew roles land in Following.미국 오피스Posted 1 month agoApply on RLWRLD's career page## Job description previewFrom RLWRLD’s original postingAbout 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...Open full posting on RLWRLD’s site