• 複数のワークフロー、システム、分野にまたがるエンドツーエンドの技術ディスカバリーを推進し、Autodeskの技術を顧客の目標に結び付ける変革機会を特定する • 高度かつ複数ソリューションにまたがる技術提案および導入パスを設計し、明確なROIストーリーとソリューション正当化資料を作成する • 技術およびビジネスのステークホルダーと長期的かつ深い関係を構築・維持し、戦略的技術アドバイザーとして機能する • 詳細なカスタマーテクニカルビジョン(CTV)を策定・維持する • マルチソリューションの拡張機会を積極的に特定し、売上成長を促進する • 複雑な技術エスカレーションをリードする • アカウントエグゼクティブと連携して案件戦略を策定する • デモ、ベンチマーキング、技術ワークショップのために社内スペシャリストを統括する • 評価結果およびパフォーマンス結果に関するデータドリブンな分析を提供する • エンタープライズイベントや業界ディスカッションにおいてAutodeskを代表する

• 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.