XPU Dev/Ops

What is XPU Dev/Ops

XPU Dev/Ops is the fusion of accelerated computing—using GPUs, TPUs, and other specialized processors—with modern DevOps practices. It addresses the infrastructure and tooling challenges of running large-scale AI, simulation, and media workflows in hybrid environments.

Why It Matters

Modern AI and scientific workloads demand far more than traditional CPUs can deliver. By integrating XPU resources with DevOps pipelines, organizations can achieve faster model training, reduced latency in inference, and seamless deployment across on-prem, cloud, or edge.

Focus Areas

• Large Language Models (LLMs): Accelerated pre-training, fine-tuning, and inference for NLP and chatbot applications.

• High Performance Computing (HPC): Simulation, computational science, and big data analytics powered by parallel processing.

• Media & Rendering: Real-time graphics, video rendering, and content pipelines enhanced by GPU acceleration.

• Simulation & Digital Twins: Physics-based modeling, scenario generation, and interactive environments powered by compute-intensive backends.

 Team Expertise

Our Multidisciplinary Team

A team of DevOps engineers, AI researchers, systems architects, and cloud specialists collaborate to optimize accelerated workflows across industries. Their combined experience ensures efficient, reliable, and scalable solutions.

Tools & Technologies

Our engineers work with tools like:
Kubernetes, Docker, ArgoCD
TensorFlow, PyTorch, ONNX
NVIDIA CUDA, ROCm, TPU SDKs
Terraform, Ansible, Jenkins
MLflow, Weights & Biases

Solutions & Services

XPU-Accelerated AI/ML Pipelines

Design and manage end-to-end pipelines for training, validating, and deploying models with XPU acceleration, whether in single-node or distributed environments.

CI/CD for GPU Workloads

Integrate model training and deployment into version-controlled pipelines with GitOps and MLOps best practices, enabling continuous improvement and rollback-safe experiments.

Hybrid & Multi-Cloud GPU Infrastructure

Provision, manage, and optimize GPU and TPU resources across cloud and on-premise environments for flexible scaling and workload portability.

Custom Dev/Ops Services

Tailored consulting and engineering support to help organizations modernize their stack with XPU-aware automation, monitoring, and security.

Case Studies

Autonomous Driving AI

Explore how accelerated computing enables real-time sensor fusion, simulation, and continuous delivery pipelines for autonomous vehicle systems.

Medical AI

Discover how healthcare and biotech sectors leverage GPUs for medical imaging, diagnostics, and compliance-bound AI pipelines.

Enterprise GenAI

Understand how enterprises deploy large-scale language models for search, customer service, and knowledge generation using cost-optimized hybrid compute strategies.

Careers

Open Positions

We’re hiring for roles that push the limits of DevOps, AI, and compute infrastructure:

• DevOps Engineer
• HPC Architect
• AI Specialist

Why Join Us

Join a forward-thinking team tackling some of the most complex problems in AI infrastructure. We offer a collaborative environment, cutting-edge projects, and growth opportunities across the DevOps and compute acceleration stack.