
Job Overview
Location
Remote
Job Type
Full-time
Category
Operations
Date Posted
April 10, 2026
Full Job Description
đź“‹ Description
- • As the Data Center RMA & Inventory Specialist at TensorWave, you serve as the logistical backbone of infrastructure operations, ensuring technicians have the components they need and managing the full lifecycle of hardware assets from receipt to secure disposal.
- • Your day-to-day responsibilities include maintaining precision inventory of critical spares, updating DCIM and ERP systems in real time, conducting physical audits, monitoring par levels, initiating and tracking RMAs with vendors, managing secure handling of failed storage media, overseeing shipping and receiving operations, coordinating with third-party vendor technicians, escorting them on the data center floor, verifying repair quality, collaborating with technicians to identify failure trends, and performing health checks on returned gear.
- • You will join a mission-driven company building a versatile cloud platform that eliminates infrastructure barriers for AI innovators, operating a growing fleet of data centers across the U.S. to power compute-intensive AI and machine learning workloads.
- • In this role, you will develop deep expertise in data center logistics, hardware lifecycle management, vendor coordination, and inventory optimization, while gaining exposure to cutting-edge GPU infrastructure and contributing directly to the reliability and scalability of AI compute services.
Skills & Technologies
About TensorWave, Inc.
TensorWave develops and operates an AI accelerator cloud built on AMD Instinct GPUs, targeting large-scale model training and inference. The platform offers on-demand and reserved compute with high-bandwidth memory, InfiniBand networking, and container orchestration, delivered through a web console and API. Designed for generative AI, LLM fine-tuning, and HPC workloads, the service emphasizes AMD performance at competitive pricing, supported by 24/7 operations teams. Based in Las Vegas, Nevada, the company serves hyperscalers, research labs, and enterprises needing GPU capacity beyond NVIDIA ecosystems.
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