New comment by Daniel_Van_Zant in "Ask HN: Who is hiring? (September 2026)"
- Status
- Open
- Remote policy
- Onsite
- Employment type
- Not stated
- Salary
- Not stated
- Source
- hn-whoishiring
- First observed
- 2026-09-12 02:11 UTC
- Last seen
- 2026-09-12 02:11 UTC
- Source claims posted
- 2026-09-12 01:29 UTC
- Consecutive misses
- 0 of 10
What the posting says
Lumen Labs | Robotics / Hardware Engineer | San Francisco, CA | ONSITE | Full-time | $130k–200k + equity | https://lumenresearch.co
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-Ro...
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.
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- x Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
-
*
#711561 2026-09-12 02:11 UTCPublished