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Robot Learning Engineer

Relling
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Hybrid (San Francisco, CA)$120k - $170k + equityFull-timePosted 5mo ago

About the role

Relling is deploying the first billion robots for manufacturing by building the deployment layer for physical AI. The role focuses on creating hybrid robotic cells that operate in real production environments and shipping reliable deployment infrastructure across the full stack (perception, motion, learned policies, observability, safety, and technician interfaces).

Responsibilities

  • Build and ship hybrid robotic cells that deploy into specialty manufacturing operations. Cells run on the floor, not in a lab.
  • Develop and extend Relling's manipulation primitive library — pick, place, insert, align, trace, press, inspect — that decomposes complex manufacturing tasks into composable, debuggable, reusable sub-skills.
  • Productize the integration tooling, safety dossier framework, and observability spine that turns one-off cell bring-ups into configuration against stable interfaces.
  • Run cells in continuous production at Fuselage and at partner sites. Diagnose failure modes that only emerge under sustained operation against real customer SKUs.
  • Distill frontier vision-language-action models for edge deployment, retaining research-grade behavior on production compute.
  • Build the technician-facing diagnostic surface that lets a maintenance technician interrogate a learned-policy cell and resolve drift without external escalation.
  • Collaborate with research partners at frontier foundation-model labs to bring their best models into production environments under real operational constraints.

Qualifications

  • Experience deploying robotic systems (classical or learned) into production environments with uptime accountability.
  • Hands-on experience across the robotics stack: motion planning, controls, perception, state estimation, runtime software, end-of-arm tooling, basic hardware bring-up.
  • Strong software engineering and infrastructure skills: data pipelines, training systems, evaluation frameworks, observability tooling, runtime monitors, fault isolation.
  • Familiarity with foundation-model robotics (VLAs, imitation learning, RL fine-tuning) and the practical engineering tradeoffs of running them on edge compute.
  • Comfort working in safety-critical environments. Familiarity with ISO 10218 / ISO TS 15066 or equivalent industrial safety standards is a plus.
  • The ability to move from a failure mode observed on the floor to a fix that ships in days rather than quarters.

Skills

Required:Robotics deployment to productionRobotics stack (motion planning, controls, perception, state estimation, runtime software, end-of-arm tooling)Software engineering and infrastructure
Nice to have:Foundation-model roboticsSafety compliance
Last updated Oct 21, 2026. Interested? Apply on the company site.
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About Relling

Data and infra for world models

Relling is working on the “ImageNet for world models”: large-scale, high-quality multimodal datasets that help AI and robotics teams train systems to see, move, and interact with the real world. We combine synchronized video, depth, LiDAR, motion, and audio, we give researchers the building blocks for truly general-purpose AI.

artificial-intelligenceroboticsinfrastructure
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