Dapster AI

Dapster AI

Lead Embedded System Software Engineer

San Francisco Bay Area

Sponsorship not specifiedDetected 1011 days ago
PythonC++LinuxEmbedded SystemsSignal ProcessingCommunicationActuators

About the role

  • This is an impact opportunity -- we're very much still an early-stage startup, and you will be working on our foundational technology and products.
  • About Dapster: Dapster is focused on bringing AI-fueled robotic picking solutions to market.
  • Broad ownership of the inner workings of the entire Dapster robotic system (we can go into much more detail live).

Responsibilities

  • We recently landed a large pilot with a top retailer -- effectively dilution-free funding to develop our core technology.

Requirements

  • Experience writing/maintaining driver-level code for different types of sensors, actuators and communication interfaces like WiFi/BlueTooth, and handling the early signal processing for these devices.
  • Ability to quickly get up to speed with an unfamiliar device by reading its specification, register map, driver api, and integrate it into the product.
  • Ability to quickly put together a circuit to electrically interface different devices.
  • A strong academic and work record (e.g. BS CS/EE with 5+ years of experience or MS CS/EE with 3+ years of experience) or commensurate work experience

Nice to have

  • Prototyping and soldering skills.

Company info

  • [Note: we are currently fully staffed for this role, but expect to be hiring for additional team members in the near future.
  • So, we likely won't review/respond quickly, but we WILL look here first when we crank up the hiring machine again.]
  • Dapster is looking for a Lead Embedded Systems Software Engineer to join our small-but-powerful team.
  • If you want to do interesting work with a sharp, experienced and humble team, and share in the upside that comes with joining at the earliest stages, we'd love to talk to you https://jobs.ashbyhq.com/Dapster.

This listing is sourced directly from Dapster AI's careers page and normalized into a canonical job model.