Job Purpose

Deliver and operate ultralowlatency, highbisection network fabrics for GPU training at ~10K GPU scale with deterministic performance.

Role Description

Key Responsibilities

- Implementation
- Build IB (HDR/NDR) eastwest fabrics and Ethernet northsouth connectivity; leafspine with ECMP.
- Deploy and tune RoCE v2, PFC/ECN, MTU, buffer profiles; IB routing/credit/timers; SHARP/UCX offloads where applicable.

- Operations

- Day2 fabric health (congestion hotspots, slowdrain, link flaps); automate config with Ansible/Terraform.
- Lifecycle of switch OS/firmware; linklevel optics and cable qualification; inventory and spares.

- Performance & Optimization

- Validate NCCL collectives performance across pods; troubleshoot allreduce bottlenecks and imbalance.
- Implement QoS classes for training vs inference vs controlplane.

- Reliability & Incident

- Lead P0/P1 critical incident response for NVIDIA GPU infrastructure, including InfiniBand, RoCE, Ethernet fabric and AI/ML cluster environments.
- Troubleshot performance bottlenecks involving InfiniBand fabrics, RoCE networks, congestion management, NCCL communications, GPUDirect RDMA, and distributed AI training workloads.
- Led post-incident reviews and implemented automation, monitoring enhancements, and architectural improvements to increase overall cluster availability, stability, and performance.
- Create runbooks for path failures, fabric partitions,



and credit starvation; design graceful degradation.

- Security & Compliance

- BGP/EVPN multitenancy, ACLs, rolebased access to fabric managers; config signing/change control.

Experience & Educational Requirements

Qualifications and Experience

EDUCATIONAL QUALIFICATIONS: (degree, training, or certification required)

BE/B-Tech or equivalent with Computer Science or Electronics & Communication

RELEVANT EXPERIENCE: (no. of years of technical, functional, and/or leadership experience or specific exposure required)

- 715 years DC networking; deep InfiniBand (HDR/NDR) and RoCE tuning at scale; GPU cluster comms patterns.

Tools / Tech

NVIDIA UFM/NetQ (or equivalent), Spectrum/Quantum families, Cumulus/Onyx/SONiC; iperf/NCCLtests; sFlow/telemetry; Ansible/Terraform.

Certifications

NVIDIA Networking; CCNP/CCIE DC; JNCIPDC / Arista ACE.

KPIs

Fabric throughput/latency SLOs, congestion events, NCCL job throughput variance, change success rate.

Work Mode

Onsite for build/turnups; oncall for P1 network incidents.

Role: Other, Industry Type: Emerging Technologies (Cloud), Department: Other, Employment Type: Full Time, Permanent Role Category: Other Education UG: B.Tech / B.E. in Any Specialization Key Skills Skills highlighted with ‘‘ are preferred keyskills NCP - AIN (AI Network Engineer)Spine-leaf Architecture expertConverge NetworkInfini band

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