Cloud Infra Engineering

Role & responsibilities

We are seeking an experienced Cloud Engineer with expertise in NVIDIA GPU technologies, Kubernetes, and cloud computing platforms (AWS, Google Cloud, Microsoft Azure) to help us design, implement, and manage scalable, high-performance infrastructure. This role is essential for building and optimizing workloads in the cloud, leveraging NVIDIA GPUs to accelerate machine learning, AI, and data science applications, and ensuring the orchestration and management of Kubernetes clusters.

Key Responsibilities:

• Design and implement cloud-native solutions using Kubernetes for orchestrating containers and deploying microservices.
• Configure and optimize cloud-based workloads for NVIDIA GPU-accelerated computing, ensuring efficient resource utilization.
• Work with cloud providers like AWS, GCP, or Azure to design scalable infrastructure solutions with GPUs for high-performance computing (HPC) and AI workloads.
• Implement and manage Kubernetes clusters using Helm charts, custom controllers, and other cloud-native technologies.
• Develop and deploy machine learning, data science, and AI models leveraging NVIDIA GPUs in a containerized environment.
• Automate deployment pipelines using CI/CD tools (e.g., Jenkins, GitLab CI, CircleCI).
• Monitor system performance, resolve issues, and maintain high availability across Kubernetes clusters in cloud environments.
• Work closely with development teams to integrate cloud-based Kubernetes clusters with various applications and workloads.
• Optimize cloud and Kubernetes cost management by using efficient resource allocation and scheduling.
• Stay up-to-date with the latest developments in NVIDIA GPUs, cloud platforms, and Kubernetes to ensure best practices and innovation.

Required Skills & Qualifications:

• Proven experience with Kubernetes and Docker.
• Experience working with cloud platforms like AWS, Google Cloud, or Microsoft Azure.
• In-depth understanding of NVIDIA GPU architecture, usage in AI/ML, and GPU resource management in cloud environments.
• Familiarity with cloud orchestration tools (e.g., Helm, Terraform, Ansible).
• Strong scripting skills (e.g., Bash, Python, Go).
• Experience with container orchestration, service discovery, and automated deployment of containerized applications.
• Knowledge of CI/CD pipelines and version control (Git).
• Excellent problem-solving skills with a focus on performance optimization and troubleshooting in a cloud environment.
• Strong communication skills to collaborate with development, operations, and data science teams.
• A degree in Computer Science, Engineering, or a related field (or equivalent work experience).

Preferred Qualifications:

• Experience with NVIDIA AI/ML frameworks (e.g., TensorFlow, PyTorch, CUDA).
• Familiarity with Istio, Prometheus, Grafana, and other Kubernetes monitoring and management tools.
• Experience with NVIDIA DGX systems or similar hardware platforms.

Preferred candidate profile

Perks and benefits