Meta
IP Validation Engineer - Machine Learning Accelerators
$178K–$250K
Sunnyvale, CA +2 · Full-time · Posted Oct 5, 2026
- Location
- Sunnyvale, CA
Redmond, WA
Austin, TX - Experience
- 8+ years of relevant experience in consumer electronics or related fields.
- Education
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
About the job
Validates and optimizes machine-learning accelerator IP across emulation, prototyping, and silicon platforms, working across hardware and software teams to resolve issues and improve performance, power, and robustness.
What you'll do
- Define and execute hardware-software integration, functional validation, and characterization plans for ML accelerator IP.
- Develop test plans, setups, and data analysis to identify risks, debug issues, and verify fixes.
- Collaborate across engineering teams and vendors to bring up ML workloads and drive cross-layer issues to resolution.
What they ask for
- Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
- Experience creating hardware-product validation plans and test methodologies.
- Experience validating ML accelerators or related programmable compute IP, including workload bring-up, functional debug, and performance characterization.
- Experience with SoC hardware interfaces such as AXI, APB, AHB, or OCP; embedded systems running RTOS, Android, or Linux; and test automation or data-processing scripting.
Nice to have
- Experience with ML frameworks, compilers, runtimes, or model-deployment workflows, including workload profiling or optimization.
- Experience with overseas development and manufacturing partners.
Pay
USD $178,000/year to $250,000/year base salary; bonus and equity amounts not stated.
Tools
AXI, APB, AHB, OCP, RTOS, Android, Linux
AI focus
Validates ML accelerator workloads and performance; the posting also asks for integrating AI tools into workflows, ongoing AI skill development, and responsible, ethical AI practices.
Model-written summary · the original posting is authoritative