What you’ll be doing...We are seeking a highly skilled AI / GPU Engineer with expertise in infrastructure and infrastructure solutions for AWS, GCP and on-premise environments. This role will focus on designing, deploying, and optimizing GPU-accelerated infrastructure to support AI/ML workloads. The ideal candidate will have deep experience with cloud-based AI infrastructure, GPU provisioning, cluster management, and performance optimization for large-scale computing environments.
Key Responsibilities
- Bare-Metal Architecture & Leadership: Drive technical strategy and infrastructure delivery for on-prem NVIDIA DGX clusters, managing hardware virtualization, Multi-Instance GPU (MIG) slicing, and GPU pooling to maximize compute utilization. Provide input and team collaboration regarding the design of bare-metal compute topologies, GPU partitioning, and hardware lifecycle management. Ability to Automate bare-metal provisioning, OS base image customization, driver updates, and multi-cluster configurations.
- Orchestration & Batch Scheduling: Lead the deployment of enterprise Kubernetes and OpenShift AI environments. Optimize workload placement using Kueue, KEDA, and custom CRDs for gang scheduling, multi-tenant GPU sharing, and event-driven autoscaling. Set platform standards for bare-metal Kubernetes, multi-tenancy access controls, and operator development.
- Advanced Inference Engine Deployment: Build enterprise-grade LLM inference architectures utilizing engines like vLLM, LiteLLM, and llm-d. Implement prefill/decode disaggregation and prefix-cache-aware routing. Architect disaggregated LLM serving pipelines, distributed KV-cache offloading, and batch job queuing.
- High-Performance Storage & Interconnects: Architect ultra-low-latency network topologies using InfiniBand and RDMA (RoCE) alongside high-throughput parallel storage systems (VAST, Weka, Ceph) to eliminate data bottlenecks during large-scale model checkpoints and training runs. Design lossless fabric topologies and high-IOPS storage for multi-node training checkpoints and dataset streaming.
- Hybrid Cloud Readiness: Design infrastructure patterns via Infrastructure as Code (Terraform, Ansible) that allow seamless bursting or workload migration to Google Cloud (GKE) and AWS (EKS) when necessary.
- Deep Telemetry & Automation: Standardize hardware-level monitoring and KPI collection using NVIDIA DCGM, Prometheus, Mimir, and Grafana. Build automated alerting and dynamic auto-remediation for failing nodes or GPU memory leaks. Establish SLA metrics, tracking cluster health down to the GPU-core level, and driving automated metric-based alerts.
- Framework Profiling: Partner with AI research teams to profile CUDA operations and optimize deep learning frameworks (PyTorch, TensorFlow, JAX) for maximum hardware-level FLOPS and throughput.
What we’re looking for...
You’ll need to have- Bachelor's degree or four or more years of work experience.
- Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training
- Knowledge of NVIDIA AI stack, including CUDA, cuDNN, TensorRT, and NVIDIA MIG.
- Experience with hybrid cloud solutions (on-prem, AWS, Google Cloud).
- Experience with DevOps & CI/CD for AI workloads, including GitOps.
Even better if you have one or more of the following:- Google Cloud Professional ML Engineer or Cloud Architect certification
- Hands-on experience with Google Cloud AI/ML offerings and on-prem GPU server deployment.
- Experience with multi-node GPU training using NCCL, MPI, or Horovod.
- Familiarity with alternative cloud providers (AWS, OCI, Azure) for AI workloads.
- Contributions to open-source AI/GPU infrastructure projects.
- Knowledge of AI security best practices (model encryption, secure AI pipelines).
If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.
In this hybrid role, you'll have a defined work location that includes working from home and a minimum of three days per week in the office, which will be set by your manager. Employees are responsible for maintaining compliance with hybrid work policies.
Scheduled Weekly Hours40
Benefits and CompensationOur benefits are designed to help you move forward in your career, and in areas of your life outside of Verizon. From health and wellness benefit options including: medical, dental, vision, short and long term disability, basic life insurance, supplemental life insurance, AD&D insurance, identity theft protection, pet insurance and group home & auto insurance. We also offer a matched 401(k) savings plan, up to 8 company paid holidays per year and up to 6 personal days per year, paid parental leave, adoption assistance and tuition assistance, plus other incentives, we’ve got you covered with our award-winning total rewards package. Depending on the role, employees have the opportunity to receive compensation in the form of premium pay such as overtime, shift differential, holiday pay, allowances, etc. Newly hired employees receive up to 15 days of vacation per year, which grows with additional service. For part-timers, your coverage will vary as you may be eligible for some of these benefits depending on your individual circumstances.
The salary will vary depending on your location and confirmed job-related skills and experience. This is an incentive based position with the potential to earn more. For part-time roles, your compensation will be adjusted to reflect your hours.
The annual salary range for the location(s) listed on this job requisition based on a full-time schedule is: $120,500.00 - $231,000.00.
