Summary:

Meta AI Research is at the forefront of advancing foundational and applied artificial intelligence, developing breakthroughs that power products used by billions of people and shape the future of human-computer interaction. We are seeking a Research Scientist at the Staff level (IC6) with deep expertise in TPU performance optimization, large-scale model training, and systems-level machine learning. In this role, you will lead high-impact research on model efficiency and optimization for first party models within Meta's native PyTorch stack, collaborating across research and engineering teams to drive AI capabilities that define Meta's next generation of products and platforms.

Required Skills:

Research Scientist, Artificial Intelligence Responsibilities:

1. Lead the design and execution of TPU performance optimization research, including kernel development, memory optimization, and compute efficiency improvements

2. Develop and optimize Pallas kernels for large-scale model training and inference on TPU architectures

3. Drive model optimization techniques including Mixture of Experts (MoE), tensor parallelism, pipeline parallelism, and other distributed training strategies

4. Optimize first party models within Meta's native PyTorch stack, ensuring efficient integration with XLA compilation and TPU execution

5. Identify and resolve complex technical challenges in model training efficiency, inference latency, and system reliability that require novel approaches

6. Define and drive multi-quarter research roadmaps for TPU optimization, aligning project milestones with broader organizational goals

7. Establish rigorous experimentation frameworks for performance benchmarking, including metric selection, profiling methodology, and data-driven optimization decisions

8. Translate research findings into production-ready optimizations by collaborating with engineering teams on deployment pipelines and reliability at scale

9. Communicate research findings and technical trade-offs clearly through publications, design documents, and presentations to both technical and non-technical audiences

10. Mentor other researchers and engineers on TPU optimization techniques, providing structured feedback on technical direction and experimental rigor

Minimum Qualifications:

Minimum Qualifications:

11. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience

12. 8+ years of experience in machine learning systems, model optimization, or high-performance computing research

13. Experience with TPU architecture and performance optimization, including profiling, kernel development, and memory management

14. Experience with XLA compilation, graph optimization, and low-level performance tuning for accelerator hardware

15. Experience developing and optimizing large-scale distributed training systems, including parallelism strategies such as data, tensor, and pipeline parallelism

16. Experience with PyTorch and its integration with accelerator backends

17. Experience communicating complex technical findings in writing, including technical reports, design documents, or peer-reviewed publications

Preferred Qualifications:

Preferred Qualifications:

18. Experience developing custom kernels using Pallas or similar kernel authoring frameworks for TPU or GPU

19. Demonstrated track record of transitioning performance research into deployed systems used at significant scale

20. PhD in Computer Science, Machine Learning, Computer Architecture, or a related technical field, or equivalent depth of research experience

21. Publication record in systems for ML venues such as MLSys, OSDI, SOSP, or related AI conferences such as NeurIPS, ICML, or ICLR

22. Experience with Mixture of Experts (MoE) architectures and their optimization for efficient training and inference

23. Experience optimizing production-scale models with billions of parameters

Public Compensation:

$184,000/year to $257,000/year + bonus + equity + 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 accommodations-ext@meta.com.