Analyze system performance bottlenecks, interoperability issues, telemetry gaps, and customer-reported issues, then feed learnings into future architecture.
Collaborate with system and cluster architects to ensure NIC/DPU features fit end-to-end AI datacenter and cloud networking designs.
What We Need To See
B.Sc. or M.Sc. in Computer Engineering, Computer Science, Electrical Engineering, or equivalent experience.
9+ years of experience in networking, system software, embedded software, firmware, or datacenter infrastructure.
Proven experience in software architecture, or technical leadership roles.
Deep understanding of networking concepts and protocols such as Ethernet, TCP/IP, RDMA/RoCE, congestion control, QoS, virtualization overlays, and traffic management.
Strong background with DPUs, SmartNICs, or other high-performance networking devices.
Experience with system management, provisioning, monitoring, telemetry, diagnostics, or lifecycle-management flows.
Familiarity with management protocols and frameworks such as Redfish, PLDM, MCTP, IPMI, gNMI, SNMP, Netconf, REST, or gRPC-based APIs.
Ability to lead cross-functional architecture discussions across software, firmware, hardware, validation, product, and customer-facing teams.
Excellent written and verbal communication skills, including the ability to create clear architecture documents and present trade-offs.
Ways To Stand Out From The Crowd
Experience defining software architecture for DPU products, including management, telemetry, QoS, performance, security, virtualization, or offload features.
Hands-on background with Linux networking, device drivers, firmware, embedded Linux, BMC software, DOCA, DPDK, OVS or Kubernetes networking.
Experience with performance counters, profiling tools, eBPF, Prometheus, Grafana, dashboards, heat maps, or large-scale telemetry systems.
Experience in defining and developing GAI-based analysis tools to extract insights from telemetry data and streams.
Background in RAS, diagnosability, serviceability, field failure analysis, production debug, or customer escalation handling.
NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the industry working with us, and we are building the networking platforms that power the AI revolution. If you are passionate about NICs, DPUs, system software, and large-scale AI networking, and you want to shape the management, telemetry, QoS, and performance architecture of future NVIDIA platforms, we want to hear from you.
