3 days ago
Base Salary
$224k - $431k/yr
Responsibilities
- Establish technical expertise in AI networking products, particularly BlueField DPU and ConnectX, and architect, design, and develop high-performance hardware-accelerated software solutions.
- Lead technical engagements with hyperscalers, including design-in, coding, bring-up, performance tuning, failure analysis, and production hardening.
- Partner with engineering, product, and architecture teams to turn customer needs into product features, reference architectures, tooling, and guidelines.
- Drive performance, reliability, and debuggability improvements across customer stacks and translate findings into product, firmware, and software roadmap items.
- Lead complex, multi-team technical initiatives and communicate technical decisions across engineers, product managers, and customer collaborators.
Requirements
- Bachelor’s, master’s, or PhD in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related science field, or equivalent experience.
- 12+ years of relevant industry experience, including technical leadership across complex systems.
- Deep knowledge of networking protocols and distributed systems, including RoCE/InfiniBand, L1–L4 fundamentals, and performance and latency tradeoffs.
- Proficiency in C/C++ and ability to debug across firmware, drivers, operating systems, and applications.
- Experience with high-performance networking and system-level debugging involving packet drops, retransmissions, congestion, QoS, ordering, and buffer management.
- Strong communication, collaboration, prioritization, and multitasking skills.
- Preferred: customer-facing technical leadership at hyperscalers or cloud service providers.
- Preferred: hands-on experience with RDMA verbs, DPDK, DOCA, NCCL, CUDA-aware networking, congestion control, performance tuning, telemetry, automation, and multi-team initiatives.
Benefits
- Competitive salary, equity, and benefits package.
- US-based role with base salary determined by location, experience, and other objective job-related factors.
- Applications accepted at least until November 9, 2026.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.