Drimva

Meta

Software Engineer, Embedded Systems

$184K–$257K

Menlo Park, CA +1 · Full-time · Posted Oct 5, 2026

Location
Menlo Park, CA
New York, NY
Experience
8+ years of experience in embedded software engineering.
Education
Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

About the job

Develop embedded systems expertise into evaluations and training data that improve Meta’s AI coding models, while doing hands-on low-level engineering across platforms.

What you'll do

  • Analyze embedded engineering challenges and create evaluations and trajectory data for model training.
  • Collaborate on AI model-building platforms for Android, Linux, and RTOSes; optimize code and review peers’ work.
  • Architect and maintain scalable systems, resolve performance issues, and provide technical guidance and mentorship.

What they ask for

  • Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
  • 8+ years of embedded software engineering, including C or C++ development for resource-constrained systems.
  • Experience across embedded platforms, including RTOS and Linux or AOSP, plus kernel internals and device-driver development.
  • Experience with embedded diagnostics, testing, and debugging; AI coding tools and responsible AI practices are also specified.

Nice to have

  • Experience collaborating with silicon or chipset vendors on firmware bring-up, reference designs, and hardware errata.
  • Experience using AI tools to accelerate embedded workflows, automate diagnostics, or improve code quality and test coverage.

Pay

$183,997/year to $257,000/year (base salary)

Tools

C, C++, Android, Linux, RTOS, Zephyr, FreeRTOS, AOSP

AI focus

Create high-quality training signals, evaluations, and trajectory data for frontier coding models; identify model improvements. The role also involves using and evaluating AI coding assistants, applying responsible AI practices, and using AI tools to improve embedded workflows.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 4, 2026 (UTC)