- Location
- San Francisco, CA, United States · Remote
- Compensation
- $50k – $120k • 0.0% – 1.0%
- Employment
- Full-time
- Experience level
- MID (2–5 years exp)
- Specialization
- Wellfound
- Source
- Wellfound
Build core runtime components that manage compute resource allocation on constrained hardware
Design and own an internal benchmarking and measurement pipeline for tracking performance and efficiency metrics over time
Work across multiple hardware targets, porting and tuning low-level control code for each
Write performance-critical C++ with Python bindings for the layer above it
Integrate with common systems-level toolchains used in embedded/robotics environments
Use AI coding tools for boilerplate, tests, and docs so your time stays on the hard problems
Requirements
Strong C++ and Python; comfortable reading driver-level / low-level system interfaces Hands-on experience with embedded or resource-constrained hardware platforms Systems thinking — you'd rather ship a measured, defensible improvement than an elegant, unmeasured one
Comfortable with ambiguity: you'll know the specifics after an NDA conversation, not before