Senior ML Accelerator IP Validation Engineer

Meta Careers; Redmond (WA); On-site; USD 178,000 - 250,000; Full time

Job summary

Meta Reality Labs is seeking an IP Validation Engineer for Machine Learning Accelerators in Redmond, WA. You will define HW-SW integration and validation plans, bring up ML workloads across emulation, prototyping, and silicon, and partner with RTL design, emulation, architecture, compiler, firmware, and system teams.

You will identify risks, develop mitigation strategies, and help optimize performance, power, and robustness of ML accelerators.

Qualifications

• 8+ years of experience in consumer electronics or related fields.
• Experience creating validation plans for hardware products including developing test methodologies for new features and technologies.
• Experience with HW-SW integration and validation of ML accelerators or related programmable compute IP.
• Experience with common SOC HW interfaces such as AXI, APB, AHB, OCP.

Responsibilities

• Define and execute HW-SW integration, functional validation, and characterization plans for ML accelerator IP across emulation, prototyping, and silicon platforms.
• Identify risks and develop mitigation strategies.
• For new technologies, define performance-power characterization and validation strategy with test plans.
• Partner with RTL design, design verification, emulation, SoC architecture, ML compiler, firmware/runtime, and system teams to bring up ML workloads and verify fixes.

Skills

HW/SW integration

Validation planning

Functional debugging

Cross-functional collaboration

AXI

APB

AHB

OCP

Tools

AXI

APB

AHB

OCP

Job description

Meta Reality Labs is seeking an IP Validation Engineer for Machine Learning Accelerators in Redmond, WA. You will define HW-SW integration and validation plans, bring up ML workloads across emulation, prototyping, and silicon, and partner with RTL design, emulation, architecture, compiler, firmware, and system teams.

You will identify risks, develop mitigation strategies, and help optimize performance, power, and robustness of ML accelerators.