This role pays more than
72%
of similar roles. Most pay
$191,468–$251,000
— the shaded band above.
At the midpoint, this role pays about
$246k
versus about
$221k
for comparable roles.
Based on 240 similar postings.
Employer
About Arm Holdings
Arm Holdings plc is a leading British semiconductor and software design firm, established in 1990 and recognized for developing energy-efficient processor architectures that power nearly all smartphones and a vast range of IoT and computing devices.
Arm Holdings currently has
48 open roles
on FindRole.
Listed pay typically runs
$209,100–$282,900
across 47 roles with salary data.
Staff Software Engineer, AI Compute Infrastructure will join the AI Compute Infra team to design, build, and operate large-scale infrastructure for AI training, fine-tuning, evaluation, and inference. The role involves building and operating Kubernetes clusters, improving workload scheduling, and enabling new CPU and GPU systems by integrating drivers, networking, storage, and monitoring. You will investigate performance issues across cloud infrastructure and hardware while partnering with AI teams to automate cluster provisioning and maintenance. Required skills include experience in Go or Python, along with practical knowledge of Kubernetes, containers, Linux, and distributed machine-learning workloads. Preferred expertise includes NVIDIA technologies like CUDA and NVLink, as well as tools such as Terraform, Argo CD, Prometheus, and Grafana. The role focuses on solving complex infrastructure challenges to improve reliability, performance, and scalability for large-scale AI compute systems.
What does a Software Engineer earn in Washington?
Median $202800 from 318 postings across 31 companies.
Build and operate large-scale Kubernetes clusters for AI training, fine-tuning, and inference.
Optimize workload scheduling, topology-aware placement, and capacity management across clusters.
Integrate and validate drivers, networking, storage, and health checks for new CPU and GPU systems.
Investigate and resolve performance and reliability issues across hardware, cloud infrastructure, and applications.
Automate cluster provisioning, upgrades, monitoring, and maintenance based on AI team requirements.
Develop reliable infrastructure software using languages like Go or Python.
Tune distributed workloads and qualify accelerators for machine learning tasks.
What we're looking for
5+ years of experience building or operating cloud, compute, HPC, or distributed infrastructure in a production environment.
Programming experience in Go, Python, or another systems language.
Practical knowledge of Kubernetes, containers, Linux, networking, and storage.
Experience supporting GPU, accelerator, or distributed machine-learning workloads.
Ability to troubleshoot complex systems and communicate clearly with engineers from different technical backgrounds.
Familiarity with Kubernetes scheduling, operators, quotas, or resource management (preferred).
Experience with NVIDIA technologies such as CUDA, NVLink, NVSwitch, NCCL, EFA, or DCGM (preferred).
Knowledge of AWS EKS, Terraform, Argo CD, Helm, Prometheus, or Grafana; familiarity with frameworks like PyTorch, Ray, vLLM, SGLang, or TensorRT-LLM (preferred).