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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Manager, Software Development - GPU... - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Expert - **Salary:** $272,000.0 - **Contract:** Permanent contract - **Skills:** C++ (Programming Language), Nvidia CUDA, Computer Programming, Databases, Data Centers, File Systems, Firmware, Field-Programmable Gate Array (FPGA), Network Protocols, Remote Direct Memory Access, Software Engineering, System Software, Data Processing, Graphics Processing Unit (GPU), Data Storage Technologies, Pytorch, Storage Technologies, Information Technology, Data Management, Nvme - **Published:** August 15, 2026 - **Apply:** https://www.juju.com/job/00000000gn537s ## About the Role + Deep knowledge of data storage platforms, databases, vector databases. + In-depth understanding of NVMe, high performance RDMA network protocols, and related technologies. + Deep understanding of system level architecture, such as topologies, interconnects, memory hierarchy, interrupts, and memory-mapped IO. + Strong interpersonal, verbal and written communications skills. + Successful experience leading team with numerous complex products, competing priorities, and successful delivery on the mission. + Bachelor's or preferably Master's or Doctoral (Ph.D) degree or equivalent experience in Computer Science, Electrical Engineering, or a related field. + 12+ overall years in the industry, including 6+ years growing, mentoring and managing teams with similar responsibilities. Ways to stand out from the crowd: + Development experience in storage software such as key-value storage, file systems, object storage systems and vector databases. + Knowledge of operating system development, including thread and process management, virtual and device memory (e.g., dmabuf), and user-level network and storage I/O. + Experience in CUDA programming, exceptional C/C++ programming skills. + Previous experience working with system software for accelerators such as GPUs, DPUs, or FPGAs. + Internals of frameworks like PyTorch and JAX. ## Description We're seeking a leader for our Data Center Storage Acceleration & Platforms team. In this role, you'll optimize NVIDIA platforms to accelerate storage access-eliminating bottlenecks by enabling direct data paths for transfers between GPU memory and storage, bypassing the CPU when possible. You'll collaborate with leaders across NVIDIA to define reference storage platform designs that integrate NVIDIA-accelerated computing into enterprise storage systems, enabling optimized data handling and delivery. What you'll be doing: + Look across the platform, from applications and frameworks to drivers and firmware - to identify software and hardware opportunities that accelerate storage performance. This includes developing new driver features, C++/CUDA libraries, and removing performance & power bottlenecks. + Drive alignment of the storage acceleration roadmap across next-generation systems, frameworks, applications, and the broader storage ecosystem. + Spokesperson for the global team, championing initiatives both internally and externally. + Lead and coordinate the planning, scheduling, and carrying out of team projects and deliverables, ensuring successful completion and accountability for the global team. + Contribute to the planning and execution of NVIDIA's reference storage platforms. ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Playing Pong on a shoulder press machine](https://www.wearedevelopers.com/videos/100140-playing-pong-on-a-shoulder-press-machine) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What’s the Difference between a Junior, Mid, and Senior Developer?](https://www.wearedevelopers.com/magazine/238-what-s-the-difference-between-a-junior-mid-and-senior-developer) - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025)