This role pays more than
91%
of similar roles. Most pay
$120,375–$178,000
— the shaded band above.
At the midpoint, this role pays about
$218k
versus about
$149k
for comparable roles.
Based on 240 similar postings.
Employer
About Broadcom
Broadcom is a global semiconductor and infrastructure software company that designs and markets a wide range of networking, storage, and wireless connectivity solutions. Industry: Semiconductors & Infrastructure Software
Broadcom currently has
123 open roles
on FindRole.
Listed pay typically runs
$121,900–$195,000
across 109 roles with salary data.
As an Applications Engineer within the Core Switching Group, you will work directly with users and internal engineering teams to deploy and support high-speed Ethernet switching designs, packet forwarding pipelines, and embedded software. You will be responsible for supporting switch and NIC solutions for HPC and AI/ML data centers while running benchmarks to tune performance metrics like congestion control, load balancing, and QoS. Your daily work involves managing SAI and SDK integration, validating features across L2/L3, VLAN, VxLAN, SRv6, and RoCE, and guiding users on RDMA and fabric design. You will utilize technical skills in Linux kernel networking, Switch Abstraction Interface API development, and telemetry-driven operations. The role focuses on solving complex problems within high-performance networking architectures, specifically addressing the infrastructure needs of GPU clusters and large-scale AI/ML data center environments.
RDMA
RoCE
TCP/IP
UDP
SONiC
Linux Networking
Ethernet
SmartNICs
DPUs
High-Speed SerDes
Packet Analysis
Telemetry
Azure
Distributed Training
Collective Communication
Congestion Control
QoS
NVIDIA
RDMA
SONiC
FBOSS
Linux
PCIe
Switching
Routing
Networking Protocols
Data Center Architecture
NICs
AI Benchmarking
HPC
Cloud Service Providers
Proof of Concept (PoC)
AI
Generative AI
Python
R
C#
Data Analytics
Algorithm Development
Software Development
System Integration
Technical Documentation
Production Software
Deep Learning
Optimization