Cloud Infrastructure & AI Compute Engineer - HPC (8-10 yrs)

Responsibilities :

- Design, deploy, and manage HPC infrastructure for running AI workloads on GPU-based environments.

- Utilize Kubernetes to orchestrate containerized AI workloads on cloud platforms (AWS, Azure, GCP).

- Optimize HPC clusters for performance, scalability, and resource utilization.

- Implement best practices for AI infrastructure security and compliance.

- Collaborate with data scientists and machine learning engineers to understand their needs and translate them into technical solutions.

- Monitor and troubleshoot infrastructure issues to ensure smooth operation of AI workloads.

- Stay up-to-date with the latest advancements in HPC, AI infrastructure, and cloud technologies.

Qualifications :

- Minimum of 8+ years of experience in cloud infrastructure engineering or a related field.

- In-depth knowledge of high-performance computing (HPC) principles and technologies.

- Proven experience with AI workloads in GPU-based environments (e.g, TensorFlow, PyTorch).

- Hands-on experience with Kubernetes on any cloud platform (AWS, Azure, GCP).

- Strong understanding of containerization technologies (Docker, container orchestration).

- Excellent problem-solving, analytical, and troubleshooting skills.

- Effective communication and collaboration skills