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Summary:

Reality Labs (RL) is responsible for delivering Meta’s vision of the next generation of wearable XR systems to enable the next great wave of human-oriented computing. The compute performance and power efficiency requirements of these future XR systems will require the best-in-class custom silicon solutions running the most efficient AI models to enable powerful new AI applications in an all-day wearable form factor. To achieve this, the Meta Silicon team is advancing the state-of-the-art across computer vision, machine learning, mixed reality, graphics, displays, sensors, and silicon systems. Our solutions will enable XR devices to deliver unprecedented machine intelligence and the most advanced silicon solutions in the industry.In this research internship, you will be responsible for research and development into the next generation AI silicon systems and design methodology for future XR systems. More specifically, you will work on formulating and developing solutions to support the deployment and optimization of AI models across XR system targets. Our internships are twelve (12) to twenty-four (24) weeks long and have various start dates throughout the year.

Required Skills:

Research Scientist Intern, Machine Learning Acceleration (PhD) Responsibilities:

1. Collaborate with computer architects, software, ML and silicon researchers and engineers, to map and optimize ML workloads on various backend targets including CPU’s, DSP’s, and Deep Learning Accelerators

2. Perform ML algorithm, software, hardware co-design to achieve best energy and performance efficiency

3. Use AI to build new solutions that aid silicon design with the goal of increasing efficiency and quality of our systems

4. Develop high performance C/C++ kernels and optimize domain specific compilers to port industry standard ML libraries to custom hardware

5. Review SOTA research trends in hardware specific ML model optimizations and mapping

6. Evaluate and integrate promising techniques into shipping products

7. Run analysis/profiling, identify performance and power bottlenecks on the actual hardware, virtual platforms, simulators or emulators and provide feedback for optimizations across the stack

Minimum Qualifications:

Minimum Qualifications:

8. Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or relevant technical field

9. Experience with Python and building complex silicon, design automation, or software systems

10. Understanding of agentic workflows and AI tools

11. Understanding of computer architecture, hardware design, and power and performance optimization fundamentals

12. Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment

13. Intent to return to degree program after the completion of the internship/co-op

Preferred Qualifications:

Preferred Qualifications:

14. Experience with design, model deployment, and performance optimization of PyTorch models for AI accelerator architectures (e.g. systolic arrays, vector extensions, custom ASICs, etc)

15. Experience applying and integrating AI to accelerate and improve hardware EDA/CAD methodology tool flows

16. Experience in LLM architectures, using LLMs to automate tasks and flows, building agentic workflows, and/or fine-tuning AI models for hardware

17. Experience or familiarity with Cadence Xtensa, Qualcomm Hexagon, or comparable digital signal processor CAD tool flows

18. Experience working in a large codebase across a large team (ex., reading and refactoring legacy code, good software development practices, etc.)

19. Experience or familiarity with Tensorflow, Pytorch, MLIR, XLA, JAX, or tensor-rt, and classic ML and CV algorithms like BERT, RNN, CNN, or similar

20. Familiarity with the state of art ML algorithm optimizations like Neural Architecture Search, quantization, pruning, or similar

21. Experience or familiarity with C/C++, Verilog, System Verilog, or VHDL

22. Familiarity with high performance software kernel development for customized ISA

23. Familiarity with code profiling and debug tools for ML

24. Experience working and communicating cross functionally in a team environment

25. Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as ISSCC, VLSI, DATE, DAC, ICCAD, ISCA, ASPLOS, MICRO, PLDI, NeurIPs, ICLR, HPCA or similar

Public Compensation:

$7,313/month to $12,134/month + benefits

**Industry:** Internet

Equal Opportunity:

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 [email protected].