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, sensors, and new ways to map the human body. Our chips will enable On-device AI assistance and features, where our real and virtual world will mix and match throughout the day. 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 work with an experienced group of researchers and engineers, and use your firmware, system integration, prototyping and hardware validation skills to implement IP validation infrastructure, bring-up IP SW workloads on prototyping and silicon platforms, and contribute to the development and optimization of state of the art machine learning accelerators. You will work closely with ML researchers, architects and designers in creating prototyping and validation requirements and test cases for multiple state of the art IPs.

Responsibilities
Support hardware system validation and performance and power characterization activities for the Electrical Engineering team
* Track test progress, document bugs, and fixes and produce regular progress reports
* Identify risks and develop mitigation strategies
* For new technologies and features, work closely with design engineering on defining performance characterization and validation strategy, as well as detailed test plans
* Work closely with the factory test team and ensure alignment of validation and characterization plans with factory 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
* Support cross functional design engineering and technology teams in driving 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 in detailed testing of at least one IP subsystem such as machine learning, display, audio, camera/vision, machine learning or wireless
* 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
* General understanding of overall hardware system architecture common to consumer electronics products
* Experience working as a hardware design or verification engineer
* Experience working with embedded C/C++ FW/HW integration
* Experience working with embedded systems that run on Android/Linux
* Python scripting experience for test automation and data processing/organization
* Demonstrated experience driving complex and ambiguous problems to solution
* Experience executing validation strategy and coordinating with cross functional teams to come up with detailed test plans for ML subsystems in products under development and work with internal and external test resources on test execution
* Experience learning quickly and extend to other areas as needed
* 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