GPU Infrastructure Architect

1 day ago


Mumbai, India Jio Full time

We are seeking an experienced AI/GPU Infrastructure Architect with Total 15 Years of experience to design and optimize GPU-based infrastructure for machine learning and artificial intelligence applications. The ideal candidate will have a deep understanding of AI workloads, GPU architecture, and infrastructure design, along with hands-on experience in deploying scalable and efficient solutions.


Key Responsibilities:

  • Architecture Design: Develop and implement architecture for AI and GPU infrastructure, ensuring scalability, reliability, and performance.
  • Infrastructure Optimization: Optimize GPU resource allocation and management to enhance performance for AI workloads.
  • Collaboration: Work closely with data scientists, software engineers, and IT teams to understand requirements and translate them into architectural solutions.
  • Performance Monitoring: Set up monitoring and benchmarking tools to assess system performance and make recommendations for improvement.
  • Research and Development: Stay updated with the latest advancements in AI and GPU technologies and assess their applicability to our infrastructure.
  • Documentation: Create and maintain architectural documentation, including design specifications, best practices, and deployment guides.
  • Security and Compliance: Ensure that infrastructure designs meet security standards and compliance requirements.
  • Training and Support: Provide guidance and training to teams on infrastructure usage and best practices.


Required Skills:

  • Proven experience as an infrastructure architect in the field of Data Centre Infrastructure (DC Rack Planning, Compute, Storage, Network) , specifically with AI and GPU technologies.
  • Strong understanding of GPU architecture and parallel processing concepts.
  • Experience of designing high performance storage solutions for AI kind of workloads with innovative solutions.
  • Knowledge of designing high performance network solutions for AI Workloads using technologies like InfiniBand, ROCE, GPU Direct etc..
  • Experience with distributed computing and microservices architecture
  • Proficiency in cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
  • Familiarity with AI frameworks (e.g., TensorFlow, PyTorch) and ML libraries.
  • Experience with system performance tuning and optimization techniques.
  • Knowledge of security best practices related to AI and infrastructure management.
  • Excellent problem-solving skills and ability to work in a collaborative environment.
  • Strong communication skills, both verbal and written.


Qualifications:

  • Bachelors in Engineers / MCA
  • Certification in relevant technologies (e.g., Azure Certified Solutions Architect, NVIDIA certifications, Certified Kubernetes Administrator).



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