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System Engineer Intern - Efficient On-Device ML Computing

AT Meta
Meta

System Engineer Intern - Efficient On-Device ML Computing

San Diego, CA

Meta Reality Labs (RL) is a pioneer in the field of Augmented Reality (AR) and Virtual Reality (VR) devices and experiences. Artificial Intelligence (AI) and on-device Machine Learning (ML) have been instrumental in driving this innovation. The Wearable System Architecture team within RL is dedicated to enhancing the power and performance of on-device ML execution through the development of custom ML accelerators, optimization of ML models, and the implementation of innovative system architectures. We are looking for skilled interns with experience in developing, profiling, and optimizing ML models for edge devices running on RTOS and AOSP. The ideal candidate will have a strong background in computing architecture, with a focus on ML accelerators and parallel computing. In this role, you will be exposed to end-to-end use case analysis and optimization, from UI to software/firmware frameworks, ML models, and underlying hardware blocks. Through detailed profiling and analysis, you will contribute to the optimization of ML models and the development of next-generation ML accelerators and Wearable system architecture.Our internships are twelve (12) to sixteen (16) weeks long.

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System Engineer Intern - Efficient On-Device ML Computing Responsibilities:
  • Perform in-depth power and performance profiling of ML models and ML benchmarks on ML accelerators.
  • Examine the power and performance characteristics of ML accelerators in relation to various types of ML models.
  • Develop an optimal mapping definition for ML models to ML accelerators.
  • Identify power and performance bottlenecks and optimization opportunities in ML models, ML accelerators, and system architectures.
  • Collaborate with cross-functional teams to prototype and productize optimizations.
  • Conduct power and performance analysis of end-to-end AI powered use cases, identify power optimization opportunities in software, firmware and overall system architecture.
  • Work alongside system architects to create a roadmap for the next generation of ML accelerators and wearable system architecture.
Minimum Qualifications:
  • Currently has, or is in the process of obtaining a Master's degree in Computer Science, or Computer Engineering with a focus on ML.
  • Proficient in ML frameworks such as PyTorch or TensorFlow.
  • Familiarity with edge ML frameworks like TensorFlow Lite or similar technologies.
  • Experienced with edge ML accelerator compiler toolchains, including ARM Vela or others.
  • Experience in embedded software development using C/C++.
  • Strong understanding of computer architecture.
  • Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
Preferred Qualifications:
  • Currently holds or is pursuing a PhD in Computer Science or Computer Engineering with a focus on ML.
  • Experience in developing and optimizing ML models for edge devices.
  • Familiarity with ML accelerators and their internal architecture.
  • Knowledge of ML model optimization techniques, such as quantization and pruning.
  • Experience with profiling ML model execution on and off-device.
  • Familiarity with power optimization techniques, such as DVFS, power and clock gating.
  • Intent to return to degree-program after the completion of the internship.
About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today-beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.

$error/year to $error/year + benefits We apologize for the inconvenience, please be patient as we work to correct the issue.

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Client-provided location(s): San Diego, CA, USA
Job ID: a1KDp00000E2O2wMAF_1002
Employment Type: Intern

Perks and Benefits

  • Health and Wellness

    • Health Insurance
    • Health Reimbursement Account
    • Dental Insurance
    • Vision Insurance
    • Life Insurance
    • Short-Term Disability
    • Long-Term Disability
    • FSA
    • FSA With Employer Contribution
    • HSA
    • HSA With Employer Contribution
    • Fitness Subsidies
    • On-Site Gym
    • Mental Health Benefits
  • Parental Benefits

    • Birth Parent or Maternity Leave
    • Non-Birth Parent or Paternity Leave
    • Fertility Benefits
    • Adoption Assistance Program
    • Family Support Resources
  • Work Flexibility

    • Flexible Work Hours
    • Remote Work Opportunities
    • Hybrid Work Opportunities
  • Office Life and Perks

    • Commuter Benefits Program
    • Casual Dress
    • Happy Hours
    • Snacks
    • Some Meals Provided
    • Company Outings
    • On-Site Cafeteria
    • Holiday Events
  • Vacation and Time Off

    • Paid Vacation
    • Unlimited Paid Time Off
    • Paid Holidays
    • Personal/Sick Days
    • Sabbatical
    • Leave of Absence
  • Financial and Retirement

    • 401(K)
    • 401(K) With Company Matching
    • Pension
    • Company Equity
    • Performance Bonus
    • Relocation Assistance
    • Financial Counseling
  • Professional Development

    • Learning and Development Stipend
    • Promote From Within
    • Mentor Program
    • Shadowing Opportunities
    • Access to Online Courses
    • Lunch and Learns
    • Internship Program
  • Diversity and Inclusion

    • Employee Resource Groups (ERG)

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