- Design, deploy, and optimize AI infrastructure solutions in the Oracle Cloud, focusing on GPU-accelerated workloads while incorporating relevant partner & open-source solutions popular in one of the sectors, such as FSI, Healthcare, Governments or high-tech/start-ups..
- Collaborate with multi-functional technical teams to design scalable and efficient architectures for AI/ML
- Provide technical expertise and support for GPU-based solutions, including performance tuning and benchmarking.
- Accelerate customer opportunities with new and existing customers through technical presentations, Proof of Concept (PoC), solution assistance. This involves driving value and innovation while focusing on sector-specific partner and open-source solutions.
- Research and evaluate emerging technologies and standard processes in AI infrastructure and GPU computing to drive continuous improvement.
- Create eloquent and compelling written assets proficiently, encompassing both external publications and internal documentation, particularly focusing on our open-source and partner solutions, benchmarks, and standard processes for running AI workloads on Oracle Cloud. Required Skills/Experience
- 8+ years of Solution Engineering experience with a Bachelor's or higher degree in Computer Science, Engineering, or related field.
- Proven experience in designing, implementing, and optimizing AI infrastructure solutions in cloud environments, with a focus on GPU workloads in one of the sectors mentioned above.
- Advanced practical knowledge of Networking, Data Center topologies, routing and switching protocols, and Ethernet/InfiniBand
- System level understanding of server architecture, PCIe devices, NICs, Linux OS, and kernel drivers. Experience with DevOps/MLOps technologies like Docker/containers, Kubernetes, data center compute/network/storage deployments.
- Proficiency in cloud platforms such as Oracle Cloud, AWS, Azure, or Google Cloud Platform, including services relevant to AI and GPU computing.
- Strong understanding of GPU architecture, CUDA programming, and parallel computing principles. Familiarity with AI frameworks and libraries (., TensorFlow, PyTorch, scikit-learn)
- Experience in deploying AI models at scale, such as transformer-based NLP models, graph-based deep learning models, and/or geometric deep learning models.
- Experience with deploying use cases such as computer vision, recommender systems, medical imaging, drug discovery, genomics, predictive analytics, financial modeling or HPC in GPU-accelerated cloud environments
- Excellent problem-solving skills and the ability to solve sophisticated technical issues in cloud-based environments and effective communication skills with the ability to collaborate across teams and convey technical concepts to non-technical key-stakeholders.
- Certifications in cloud computing (., Oracle Cloud Infrastructure Architect Associate, AWS Certified Solutions Architect, Azure Solutions Architect) and GPU computing (., VIDIA Certified Associate – AI in the Data Center) are a plus.
- Background with open-source development with a Proficiency in systems engineering, coding (C/C++, Python, CUDA)
- Hands-on experience with NVIDIA systems/SDKs (., Triton Inference Server), NVIDIA Networking technologies (., DPU, RoCE, InfiniBand), and/or AMD GPU solutions.
- Relevant publication history and/or conference attendances. Occasional travel required for local on-site visits to customers and industry events.
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Architect Specialist AI Infrastructure GPU - Dubai, United Arab Emirates - Oracle
Description
Engages with strategic customers, builds leadership relationships at multiple levels within organizations in order to design and implement solutions. Works directly with customers to gather requirements, develop architectures and translates business needs into solutions. May implement solutions and ensure successful deployments through code development and scripting. Displays product/application understanding through highly customized presentation demonstrations to customers, and at conferences, and events. Supports customer from Proof of Concept (POC) through production deployment of services via resource configuration, planning, and customer education/training. Creates and distributes technical assets (white papers, solution code, blog posts, and video demonstrations). Serves as a leading contributor for customers and sales on technical cloud solutions and customer success. Identifies gaps and enhancements to influence engineering roadmaps for customer driven features. Leading contributor, may provide direction and mentoring to others. Work is non-routine and very complex, involving the application of advanced technical/business skills in area of specialization. May interact with C level. Maintains expertise by staying current on emerging technologies.
