Description review

Lumen Labs | Robotics / Hardware Engineer | San Francisco, CA | ONSITE | Full-time | $130k–200k + equity

Lumen Labs · San Francisco, CA · back to the listing

HR standards

64/100

needs work

Title ↔ description

79/100

solid

Reads as

Unclear

no confident match

What the listing never says

  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency
  • No location or timezone policy stated, so a candidate cannot tell where they may work from. Scope clarity

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

I'm Daniel, co-founder. Lumen Labs is building the cognitive layer for physical AI. Nearly every major robotics effort today teaches machines by showing them thousands of hours of human teleoperation. We think that paradigm has a ceiling, and we're working on nature-inspired architectures for unstructured environments (construction sites, mining, pipelines, battlefield). Pre-seed, backed by top VC funds and operators from robotics/AI companies.
We're a team of two and hiring teammate #3 to own the hardware and infrastructure that keeps our research platforms running: the ROS2 (Humble) stack across onboard and offboard compute, sensor integration and calibration (LiDAR, depth, IMU, encoders), the safety pipeline during autonomous runs, and getting trained policies onto real hardware. Today that's wheeled navigation; we're dipping our toes into drones and eyeing weirder platforms like pipeline inspection. Where we're at: zero-shot sim2real transfer with a policy that runs at 100Hz on an ESP32 and took under a day to train.
You: hands-on with real mobile robots (UART, encoders, PWM, IMU, LiDAR), strong Python + embedded, comfortable reading code you didn't write, and can debug hardware and firmware at the same time. If "full-stack" to you means firmware, a multimeter, and a ROS node in the same afternoon, you'll fit right in. Visa/relocation support for the right person.
Full posting: https://desert-bearskin-26d.notion.site/Robotics-Engineer-Robot-Wrangler-Lumen-Labs-3d8e2e6bfecb80b6ba9ede7b09b31a4c?source=copy_link
Email [email protected], mention HN, and tell us about a project you've built. If you can link to a time you got a trained policy running on real hardware, you go to the top of the pile.

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 16 points (from 80 before penalties). Reviewed 21 Sep 2026.