• Building and maintaining a long-term technology stack with well defined APIs that is service-oriented, modular, granular, observable, and efficient. • Working closely with data scientists, product managers and other XFN partners to build business insights, develop product features and respond to fraud attacks and risk issues across the platform. • Building and maintaining integrations with third party vendors / payments networks & processors to empower our in house chargeback defense systems. • Developing and iterating on our dispute & chargeback mitigation and remediation strategies as risk scenarios/business requirements evolve. • Focusing on continuous monitoring and alerting to uplevel the quality and observability of our risk systems. • Collaborating with other engineering teams across Airbnb to advance our engineering process and technical foundation.

• Responsible for NVIDIA board team product management, including product yield management, drives and ensure product engineering implementation, maintenance of manufacturing methods, processes, and operations for new and existing products, product change control and build management, product failure debug and resolution over TOP issues. • Supervise NVIDIA board products’ quality and yield goals, and take corrective actions if needed. • Work with hard design, validation, software and product engineers to characterize product, address bugs, improve product quality. • You will be onsite support over global CM sites.

• Establish groundbreaking performance benchmarking methodologies and analysis workflows and identify performance issues and opportunities for NVIDIA’s inference ecosystem (e.g. TensorRT/TensorRT-EdgeLLM/Torch-TensorRT) • Contribute features and code to NVIDIA/OSS inference frameworks including but not limited to TensorRT/TensorRT-EdgeLLM/Torch-TensorRT. • Develop new model pipelines for NVIDIA’s inference ecosystem with optimized performance including but not limited to areas like quantization, scheduling, memory management, and distributed inference to set the gold standard for Gen AI performance. • Work with cross-collaborative teams inside and outside of NVIDIA across generative AI, automotive, robotics, image understanding, and speech understanding to set directions and develop innovative inference solutions. • Scale performance of deep learning models across different architectures and types of NVIDIA accelerators.

• Performance optimization, analysis, and tuning of LLM, VLM and GenAI models for DL inference, serving and deployment in NVIDIA/OSS LLM frameworks • Scale performance of LLM models across different architectures and types of NVIDIA accelerators • Scale performance for max throughput, minimum latency and throughput under latency constraints • Contribute features and code to NVIDIA/OSS LLM frameworks, inference benchmarking frameworks, TensorRT, and Triton • Work with cross-collaborative teams across generative AI, automotive, image understanding, and speech understanding to develop innovative solutions