XPU Dev/Ops

What is XPU Dev/Ops?

XPU Dev/Ops is a specialized discipline that integrates DevOps principles with accelerated computing technologies—including GPUs, TPUs, and other XPUs—to support AI-driven workflows, compute-heavy simulations, and next-gen digital experiences. It’s not just DevOps—it’s DevOps optimized for high-speed, intelligent, and scalable execution.

Why It Matters

Traditional DevOps practices can struggle to handle the scale and complexity of AI and simulation workloads. XPU Dev/Ops bridges this gap by enabling rapid deployment, performance tuning, and lifecycle management of high-throughput, low-latency systems. Whether you're building LLMs, training neural networks, or running digital twins, XPU Dev/Ops ensures optimal performance and delivery.

XPU Focus Areas

• Large Language Models (LLMs): Scalable training and inference environments tailored for modern AI applications.
• High Performance Computing (HPC): Optimized infrastructure for compute-intensive simulations and analytics.
• Media & Rendering: Real-time rendering pipelines and accelerated media processing in hybrid cloud setups.
• Simulation: Support for physics-based simulations, digital twins, and immersive environments across industries.

Team Expertise

Our Multidisciplinary Team

We’re a collective of DevOps engineers, system architects, data scientists, and AI researchers with deep experience in performance engineering, MLOps, and cloud orchestration. Together, we build infrastructure that can think, scale, and evolve.

Tools We Use

• Kubernetes, Docker, Terraform
• NVIDIA CUDA, cuDNN, TensorRT
• PyTorch, TensorFlow, HuggingFace
• Jenkins, GitLab CI/CD
• Prometheus, Grafana, ArgoCD
• Cloud Platforms: AWS, GCP, Azure

Partnerships & Certifications

• NVIDIA Inception Partner
• Google Cloud AI Certified
• Red Hat Certified Engineers
• VMware & Kubernetes Ecosystem Integrations

Solutions & Services

XPU-Accelerated AI/ML Pipelines

We design, deploy, and optimize AI/ML pipelines that harness XPU acceleration for faster model training, lower inference latency, and scalable performance in production environments.

CI/CD for GPU Workloads

Automated workflows that integrate GPU-aware testing, deployment, and scaling—ensuring high-efficiency DevOps for AI/ML, media processing, and scientific computing.

Hybrid & Multi-Cloud GPU Infrastructure

Seamless orchestration of GPU resources across private and public clouds for always-available, elastic, and cost-optimized operations.

Custom Dev/Ops Services

Need something tailored? We offer architecture consulting, XPU cluster setup, and long-term Dev/Ops collaboration for enterprises innovating with AI, simulation, or real-time media.

Case Studies

Autonomous Driving AI

How high-throughput XPU architectures enable rapid training of perception models, real-time simulation, and CI/CD deployment pipelines for autonomous driving platforms. Focus areas include sensor fusion, path planning, and neural network optimization.

Medical AI

Exploring the role of GPU/TPU-accelerated pipelines in diagnostics, image segmentation, and predictive analytics. Emphasis on secure data environments, regulatory compliance, and low-latency inference at the edge.

Enterprise GenAI

Large Language Models (LLMs) are transforming enterprise workflows—from customer support to knowledge base generation. This case explores how enterprises leverage multi-GPU infrastructure, orchestration tools, and cost-effective scaling across hybrid environments.

Careers

Open Positions

We're growing. Join us in shaping the future of accelerated DevOps:

• DevOps Engineer
• HPC Architect
• AI Specialist

Why Join Us

At Cloudaron, you’ll work on real-world AI and HPC problems, side by side with innovators in the XPU space. We value creativity, autonomy, and impact—and we provide the tools, mentorship, and flexibility to make your best work happen.