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Job Description
- Drive the definition and optimization of the hardware/software stack to enable performant training and serving of large ML models.
- Collaborate with research and modeling teams to innovate on model architectures, focusing on scaling, quality, and their direct impact on hardware performance.
- Lead the development of configurable architectural simulators and cycle-accurate performance models to quantify microarchitectural optimizations and evaluate architectural decisions.
- Conduct system-level performance analysis across highly distributed ML systems, innovating new methodologies to balance compute, memory bandwidth, and inter-chip network requirements.
- Engage with partners across hardware design, compiler development, and ML research to transition architectural innovations from concept to production.