TensorWave
TensorWave builds an AMD‑exclusive cloud platform for AI workloads, providing Instinct MI325X and MI355X GPU instances and tooling for training, fine‑tuning, and inference, including an inference engine. It sells infrastructure-as-a-service to startups and enterprises that need scalable AI compute. Founded in 2023 and headquartered in Las Vegas, Nevada, the company focuses on GPU‑accelerated cloud infrastructure for generative AI and machine learning teams.
Open Positions at TensorWave
7 open positions
Senior Network Automation Engineer responsible for designing scalable automation systems that deploy, manage, and operate large-scale AI network fabrics. The role combines network lifecycle automation, validation, configuration management, and CI/CD workflows across multi-vendor environments.
Build and lead the ground-up rebuild of TensorWave’s internal tools and customer-facing dashboards for its AI cloud platform. This full-stack role spans React and Next.js frontends, Node.js and Go backend services, APIs, and observability.
Lead the architecture, evolution, and operational reliability of TensorWave’s multi-region Kubernetes platform at scale. This senior staff role focuses on control plane design, multi-tenancy, networking, observability, incident response, and resilient AI infrastructure.
TensorWave is hiring a senior Front-End Software Engineer to build high-performance customer and internal dashboards for real-time GPU telemetry. The role centers on TypeScript, React, reusable component systems, data visualization, and frontend architecture.
Staff Database Engineer responsible for architecting, operating, and scaling highly available database platforms that support TensorWave’s AI compute infrastructure. The role combines deep PostgreSQL and MySQL performance engineering with observability, automation, incident leadership, and technical mentorship.
Lead the design and evolution of a large-scale virtualization platform powering GPU-intensive AI workloads across multiple data centers. This hands-on infrastructure role focuses on KVM/QEMU, Linux systems, performance isolation, automation, and resilient platform architecture.
Build and operate the ML infrastructure powering distributed training and inference across TensorWave’s large-scale GPU cloud platform. This senior role focuses on reliable workload orchestration, performance, scalability, and developer experience.