IP Validation Engineer - Machine Learning Accelerators

Reality Labs focuses on delivering Meta's vision through On-device AI. The compute performance and power efficiency requirements of these workloads require custom silicon. Reality Labs Silicon team is driving the state of the art forward with breakthrough work in computer vision, machine learning, mixed reality, displays and sensors. Our chips enable On-device AI assistance and personal superintelligence features, contextualized to timing and personalized requirements. We believe the only way to achieve our goals is to look at the entire stack, from transistors to architecture, firmware, and algorithms.

As a Machine Learning IP Validation Engineer at Meta Reality Labs, you will use your hardware/software integration, prototyping, emulation, firmware, and hardware validation skills to develop IP validation infrastructure; bring up, validate, and optimize ML workloads across pre-silicon and post-silicon platforms; and improve the functionality, performance, power, and robustness of state-of-the-art ML accelerators. You will partner cross-functionally with RTL design, verification, emulation, architecture, ML compiler, firmware/runtime, and ML model teams to define validation requirements, debug cross-layer issues, and drive them to resolution.

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 and features, work closely with design engineering on defining performance-power characterization and validation strategy, as well as detailed test plans
Participate in design reviews and make recommendations to support overall test strategy
Create test setups, collect and analyze data to help debug technical issues
Partner with RTL design, design verification, emulation, SoC architecture, ML compiler, firmware/runtime, and system teams to bring up ML workloads, identify root causes, drive cross-layer issues to resolution, and verify fixes
Convert large amounts of data into a clear summary to communicate to stakeholders at all levels

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
8+ years of relevant 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, including workload bring-up, functional debug, performance characterization
Familiar with testing common SOC HW interfaces such as AXI, APB, AHB, OCP
Experience in troubleshooting with component vendors on test escapes, missing test coverage, etc Demonstrated experience supporting technical teams, cross-functional groups and vendors to execute against validation plans
Demonstrated understanding of consumer electronics product lifecycle, development process and partner eco-system
Experience working as a verification or systems engineer
Experience working with embedded systems that run on RTOS/Android/Linux
Scripting experience for test automation and data processing/organization
Experience with ML frameworks, compilers, runtimes, or model-deployment workflows, including profiling or optimizing ML workload performance, data movement, memory behavior, or power
Proven communication and collaboration skills and experience communicating and driving issues to resolution across cross functional teams
Experience working with overseas development and manufacturing partners
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies