# Technical NIC & DPU Performance Research & Analysis Engineer

**Company**: NVIDIA
**Location**: Yokneam, Israel
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Israel-Yokneam/Senior-Performance-Research-and-Analysis-Engineer_JR2028611?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_6a999ff8-f19

## Description

NVIDIA's Performance Group is seeking a technical NIC & DPU Performance Research & Analysis Engineer to drive end-to-end performance strategy, characterization, optimization, and HW offload accelerations for next-generation network interfaces and Data Processing Units (DPUs).

In this role, you will analyze and accelerate critical networking and storage technologies and protocols powering multi-node AI clusters. You will profile performance across the complete hardware-to-software execution stack,stretching from DPU Arm CPU subsystems and PCIe to high-speed RDMA, SPDK, and DOCA acceleration pipelines.

**Responsibilities**

- Data-Path Optimization: Drive end-to-end benchmark plans, performance characterization, expectations, and optimizations for NICs and DPUs deployed in distributed AI and cloud data centers.

- Full-Stack Profiling: Profile low-level memory, PCIe, host CPU, and DPU ASIC execution paths to identify micro-architectural stragglers, queue bottlenecks, and tail-latency outliers.

- Storage & Network Acceleration: Hands-on acceleration and offloading of storage (SPDK, NVMe-oF, VirtIO) and networking protocols (RDMA/RoCEv2, TCP/IP, DOCA).

- AI-Assisted Workflow Automation: Leverage AI agents, autonomous scripts, and automated regression frameworks to scale continuous performance evaluation.

- Cross-Functional RCA: Partner closely with Architecture, ASIC, Firmware, and Software engineering groups to conduct rigorous Root Cause Analysis (RCA) and establish performance targets for upcoming pre- and post-silicon platforms.

**Requirements**

- B.Sc. or M.Sc. in Computer Science, Computer/Electrical Engineering, Software Engineering, or equivalent practical experience.

- 5+ years of experience in low-level networking, storage acceleration, and systems-level performance tuning in cloud or HPC environments.

- Direct hands-on experience with at least two of the following: DOCA, SPDK, VirtIO, RDMA/RoCEv2, TCP/IP.

- Strong programming proficiency in C, Python, and Linux shell scripting (Bash).

- Micro-architectural understanding of modern CPU/ASIC memory hierarchies, PCIe Gen 5/6 interconnects, and Linux kernel networking stacks.

- Proven track record using AI coding agents or automated script generators to streamline daily engineering workflows.

**Preferred Qualifications**

- Deep hands-on experience tuning NVIDIA BlueField DPUs, ConnectX SmartNICs, or custom hardware offload engines.

- Mastery of the full SPDK & NVMe-oF (NVMe over Fabrics) storage stack over high-speed RDMA transport layers.

- Comprehensive system-level understanding across x86 (Intel/AMD) and Arm architectures, PCIe topology, and GPUDirect Storage (GDS).

- Proven experience isolating stragglers and tail latency in multi-tenant, cloud-scale environments.

## Skills

### Required
- C
- Python
- Linux shell scripting
- DOCA
- SPDK
- VirtIO
- RDMA/RoCEv2
- TCP/IP

### Nice to have
- NVIDIA BlueField DPUs
- ConnectX SmartNICs
- SPDK & NVMe-oF
- GPUDirect Storage

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Israel-Yokneam/Senior-Performance-Research-and-Analysis-Engineer_JR2028611?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)