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Selected role

Research Scientist Intern, PyTorch Framework Performance (PhD)

Meta Bellevue, WA, US

$91k - $145k Senior Full-time

Our team’s mission is to make PyTorch models high-performing, deterministic and stable, via a robust foundational framework that supports the latest hardware, without sacrificing the flexibility and ease of use of PyTorch.We are seeking a PhD Research Intern to work on next-generation Mixture-of-Experts (MoE) systems for PyTorch, focused on substantially improving end-to-end training and inference throughput on modern accelerators (e.g., NVIDIA Hopper and beyond).This internship will explore novel combinations of communication-aware distributed training and kernel- and IO-aware execution optimizations (inspired bySonicMoE and related works) to unlock new performance regimes for large-scale sparse models. The project spans systems research, GPU kernel optimization, and framework optimization, with opportunities for open-source contributions and publication.Team scope:- Improve PyTorch out-of-the-box performance on GPU, CPU, accelerators- Vertical performance optimization for models for training and inference- Model optimization techniques like quantization for improved efficiency- Improve stability and extensibility of the PyTorch frameworkOur internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, PyTorch Framework Performance (PhD) Responsibilities:

Design and evaluate communication-aware, kernel-aware, and quantization-aware MoE execution strategies, combining ideas such as expert placement, routing, batching, scheduling, and precision selection.
Develop and optimize GPU kernels and runtime components for MoE workloads, including fused kernels, grouped GEMMs, memory-efficient forward and backward passes.
Explore quantization techniques (e.g., MXFP8, FP8) in the context of MoE, balancing accuracy, performance, and hardware efficiency.
Build performance models and benchmarks to analyze compute, memory, communication, and quantization overheads across different sparsity regimes.
Run experiments on single-node and multi-node GPU systems.
Collaborate with the open-source community to gather feedback and iterate on the project.
Contribute to PyTorch (Core, Compile, Distributed) within the scope of the project.
Improve PyTorch performance in general.

Minimum Qualifications:

Currently has, or is in the process of obtaining, a PhD degree in the field of Computer Science or a related STEM field
Deep knowledge of transformer architectures, including attention, feed-forward layers, and Mixture-of-Experts (MoE) models
Strong background in ML systems research, with domain knowledge in MoE efficiency, such as routing, expert parallelism, communication overheads, and kernel-level optimizations
Hands-on experience writing GPU kernels using CUDA and/or cuteDSL
Working knowledge of quantization techniques and their impact on performance and accuracy
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

Familiarity with distributed training and inference, such as data parallelism and collective communication
Ability to independently design experiments, analyze complex performance tradeoffs, and clearly communicate technical findings in writing and presentations
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 NeurIPS, MLSys, ASPLOS, PLDI, CGO, PACT, ICML, or similar
Experience working and communicating cross functionally in a team environment

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 [email protected].

$7,650/month to $12,134/month + benefits

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.

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