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The role involves managing sales strategies, analyzing market data, improving customer relations, and executing revenue maximization plans.

The role involves adapting PyTorch for specific hardware, building kernel DSLs, designing scheduling passes, and contributing to open-source projects related to AI/ML workloads.

Build and operate representative LLM and distributed AI environments, collect traces and telemetry, develop benchmarks, and identify performance bottlenecks across compute, memory, interconnect, and scheduling. Profile and optimize workloads on NVIDIA GPU platforms, analyze large-scale distributed AI performance, and collaborate with hardware and software teams to guide hardware-software co-design for next-generation AI platforms.

Research and develop next-generation embedded memory firmware and architectures. Design, code, validate, and fine-tune firmware; perform lab bring-up and server integration; validate hardware IPs in virtual environments; develop HAL APIs and RTOS-based embedded memory software. Collaborate with cross-functional teams, customers, and partners throughout development and integration.