Senior Cloud HPC Engineer

As a Senior Cloud HPC Engineer at Qvelo, you will play a crucial role in architecting, deploying, and optimizing high-performance computing (HPC) environments on cloud platforms. This role involves leveraging cloud technologies to build scalable, secure, and high-performance HPC solutions for complex workloads such as simulations, machine learning, big data analytics, and scientific research. You will collaborate with cross-functional teams, providing expertise in cloud-based HPC infrastructure, system integration, and performance tuning, helping clients maximize the value of their cloud HPC deployments.

Key Responsibilities:

• Lead the design and architecture of cloud-based HPC solutions across platforms such as AWS, Azure, and Google Cloud.
• Deploy and configure cloud HPC environments that support data-intensive applications, AI/ML workloads, and large-scale simulations.
• Optimize HPC infrastructure for scalability, performance, and cost-efficiency, ensuring seamless integration with on-premises and hybrid HPC systems.
• Implement and manage high-performance storage solutions in the cloud, including parallel file systems and distributed storage architectures.
• Leverage cloud-native technologies like containers, Kubernetes, and serverless architectures to enhance the flexibility and agility of cloud HPC environments.
• Configure and tune high-speed networking solutions in cloud environments, ensuring low-latency communication between compute nodes and storage.
• Design and deploy automation frameworks to streamline the provisioning, scaling, and monitoring of cloud HPC resources.
• Ensure security best practices are followed when deploying HPC clusters in the cloud, including data encryption, access control, and secure networking.
• Collaborate with DevOps teams to create automated CI/CD pipelines for HPC applications, enabling rapid deployment and updates.
• Monitor and troubleshoot cloud-based HPC systems, identifying performance bottlenecks and ensuring optimal resource utilization.
• Provide expertise in cloud cost management, optimizing the use of cloud resources to minimize costs while maintaining performance.
• Mentor and guide junior engineers and technical staff, providing leadership on cloud HPC technologies and best practices.
• Stay updated on emerging cloud and HPC technologies, incorporating the latest advancements into client solutions and internal infrastructure.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• 5+ years of experience in architecting and managing HPC environments, with a strong emphasis on cloud-based HPC systems.
• Proven expertise in cloud platforms such as AWS (with services like EC2, S3, FSx for Lustre), Microsoft Azure (Azure Batch, Azure HPC Cache), or Google Cloud (Google Cloud HPC).
• Deep knowledge of cloud-native technologies such as containers (Docker, Singularity), Kubernetes, and orchestration tools for HPC environments.
• Experience with high-performance interconnects (InfiniBand, RoCE) and optimizing network configurations in cloud environments.
• Proficiency in configuring and managing parallel file systems (Lustre, GPFS) and distributed storage systems in the cloud.
• Strong knowledge of cloud cost optimization strategies, including right-sizing instances, leveraging spot instances, and automating scaling policies.
• Experience with automation and scripting (e.g., Terraform, Ansible, Python, Bash) for cloud resource provisioning, monitoring, and scaling.
• Familiarity with cloud security best practices, including data encryption, secure access controls, and compliance with industry standards.
• Strong problem-solving skills, with experience in troubleshooting and optimizing HPC applications for cloud environments.
• Excellent communication and collaboration skills, with the ability to work with both technical and non-technical stakeholders.

Preferred Qualifications:

• Certification in cloud platforms such as AWS Certified Solutions Architect, Azure Solutions Architect Expert, or Google Cloud Professional Architect.
• Experience with hybrid HPC architectures, integrating cloud and on-premises HPC systems.
• Knowledge of AI/ML workloads in cloud HPC environments, including deep learning frameworks (TensorFlow, PyTorch) and GPU-accelerated computing.
• Familiarity with quantum computing technologies and their integration into cloud-based HPC solutions.
• Experience with DevOps practices in cloud environments, including CI/CD for HPC applications and infrastructure-as-code (IaC) principles.