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Meta · 6 hours ago

Research Scientist Intern, Machine Learning Acceleration (PhD)

Sunnyvale, CA

Internship

Onsite

Intern

$7,313/mo - $12,134/mo

Meta is a technology company focused on building immersive experiences that connect people and communities. The Research Scientist Intern will be responsible for researching and developing next-generation AI silicon systems and design methodologies to optimize AI models for XR systems.

Computer Software

Comp. & Benefits

Responsibilities

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

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

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

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

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

Evaluate and integrate promising techniques into shipping products

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

Qualification

Machine LearningC/C++ DevelopmentSilicon DesignComputer ArchitecturePythonPyTorchTensorFlowAI Model OptimizationResearch SkillsTeam CollaborationCommunication Skills

Required

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

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

Understanding of agentic workflows and AI tools

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

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

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

Preferred

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

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

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

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

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

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

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

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

Familiarity with high performance software kernel development for customized ISA

Familiarity with code profiling and debug tools for ML

Experience working and communicating cross functionally in a team environment

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