Company Overview

Jio, a leader in the telecommunications and digital services industry, empowers India's leading telecom operator with over 400 million customers. We have developed an array of cloud-native solutions spanning 5G technology, AI/ML platforms, and BSS solutions that enable seamless service delivery. With a focus on both B2C and B2B markets, our innovative solutions enhance functionality, scalability, and customer engagement. Headquartered in Navi Mumbai, Jio continues to revolutionize digital infrastructure in India.

Job Overview

We are seeking a Senior Subject Matter Expert in AI Infrastructure Implementation to join our dynamic team in Mumbai. This full-time role demands a strategic thinker with an in-depth understanding of AI/ML platforms and cloud-native infrastructure deployment.

Skills Required:

• Extensive experience in implementing and managing Data Centre Infrastructure (Compute, Storage, Network) specifically with GPU infrastructure for AI and machine learning applications.
• Prior experience of implementation of GPU based compute infrastructure (HP, Dell, NVIDIA DGX, Liquid Cool Systems)
• Must have deployed high performance storage solutions (VAST, WEKA, DDN, GPU Direct Storage) for AI workloads (Training and Inference)
• Should have knowledge of high-performance network solutions implementation (InfiniBand, ROCE, NDR / HDR).
• Strong understanding of GPU architecture and its application in AI workloads.
• Proficiency in cloud platforms (e.g., AWS, Azure, Google Cloud), Kubernetes and virtualization technologies.
• Familiarity with AI frameworks (e.g., TensorFlow, PyTorch) and orchestration tools (e.g., Kubernetes).

Roles and Responsibilities

• Implementation Leadership: Lead the implementation of GPU infrastructure solutions for AI and machine learning workloads, ensuring alignment with organizational goals.
• Configuration Management: Configure and optimize hardware and software components, including GPUs, servers, Storages and networking, to maximize performance and efficiency.
• Collaboration: Work closely with cross-functional teams, including data scientists, software developers, and IT operations, to understand requirements and ensure seamless deployment.
• Best Practices Development: Establish and document best practices for GPU infrastructure implementation, including performance tuning, resource allocation, and troubleshooting.
• Training and Support: Provide training and support to team members on GPU infrastructure setup, management, and optimization techniques.
• Performance Analysis: Monitor system performance and conduct benchmarking tests to identify bottlenecks and recommend improvements.
• Technical Guidance: Serve as a technical advisor on AI and GPU-related projects, providing insights and recommendations based on industry standards and emerging technologies.
• Continuous Improvement: Stay abreast of advancements in AI and GPU technologies, evaluating their impact on current infrastructure and proposing enhancements.

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