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Solutions Engineer

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Remote

Solutions Engineer

Moondream AI

Solutions Engineer

Skills

Python

14 days ago

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Important information


Contract type:

Permanent

Location:

San Francisco, CA, USA

Work mode:

Remote

Published on:

9 October 2026

What they need


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Solutions Engineer

San Francisco, CA·In-person·Full-time

Every Moondream deal has a moment where the customer says “okay, but will this actually work on our hardware, with our cameras, in our network?” The AE looks at you. That's the job.

Our customers are running vision models on NVIDIA Jetson at the edge, in locked-down private clouds, on bare metal behind firewalls that block everything interesting. One has RTSP streams from fifteen different camera models and a network engineer who doesn't return emails. You figure out the integration path, build the proof of concept, and make it work in their environment, not a clean demo on your laptop.

You Should Probably Apply If

  • You've done pre-sales or solutions engineering and your POCs actually turned into production deployments
  • You can write a working integration in Python or C++ while screen-sharing with a customer and not break a sweat
  • You've debugged problems that span video pipelines, networking, hardware, and deployment tooling, ideally all in the same afternoon
  • You've worked with on-prem deployments and know why “just use the cloud” makes infrastructure teams stop returning your calls

You Should Definitely Not Apply If

  • You scope the demo and then hand it to someone else to build
  • You haven't touched a terminal in your last role
  • Remote work is non-negotiable (we're in-person in San Francisco because the best solutions get built when you can grab someone from engineering and whiteboard it out)

What you'll actually do

  • Own the technical side of deals from first call to deployment. Understand the customer's video pipeline, infrastructure constraints, and what they actually need (which is rarely what they say they need).
  • Build POCs that prove Moondream works in the customer's actual environment: their cameras, their hardware, their network
  • Debug across the full stack: model inference, video ingest, container orchestration, bare-metal quirks, and whatever else is between us and production
  • Feed real customer problems back to engineering so the product gets better, not just the slide deck
  • Spend a Tuesday afternoon SSH'd into a customer's edge device wondering why GStreamer hates their particular camera firmware

Details

  • Location: San Francisco, CA (in-person)
  • Compensation: $120k–$150k base + $35k–$55k variable + meaningful equity
  • Benefits: Health, dental, vision, paid parental leave, relocation support

Apply

Send your resume to [email protected]

Expect to hear back within a week. If you don't, please follow up!

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