AI Technical Specialist **General Information** Req # WD00077661 Career area: Sales Support Country/Region: Malaysia State: Wilayah Persekutuan Kuala Lumpur City: Kuala Lumpur Date: Monday, March 10, 2025 Working time: Full-time **Additional Locations** : * Malaysia **Why Work at Lenovo** We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US$57 billion revenue global technology powerhouse, ranked #248 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY). This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com , and read about the latest news via ourStoryHub (https://news.lenovo.com/) . **Description and Requirements** **Key Responsibilities** : AI Production Deployment: + from testing to final deployment. + Configure, install, and validate AI systems using key platforms, including: + VMware ESXi and vSphere for server virtualization, Linux (Ubuntu/RHEL) and Windows Server for operating system integration, + Docker and Kubernetes for containerization and orchestration of AI workloads. + Conduct comprehensive performance benchmarking and AI inferencing tests to validate system performance in production. + Optimize deployed AI models for accuracy, performance, and scalability to ensure they meet production-level requirements and customer expectations. **Technical Expertise** : + Serve as the primary technical lead for the AI POC deployment in enterprise environments, focusing on AI solutions powered by Nvidia GPUs. + Work hands-on with Nvidia AI Enterprise and GPU-accelerated workloads, ensuring efficient deployment and model performance using frameworks such as PyTorch and TensorFlow. + Lead technical optimizations aimed at resource efficiency, ensuring that models are deployed effectively within the customer’s infrastructure. + Ensure the readiness of customer environments to handle, maintain, and scale AI solutions post-deployment. **Project Management** : + Assume complete ownership of AI project deployments, overseeing all phases from planning to final deployment, ensuring that timelines and deliverables are met. + Collaborate with stakeholders, including cross-functional teams (e.g., Lenovo AI BDMS, solution architects), customers, and internal resources to coordinate deployments and deliver results on schedule. + Implement risk management strategies and develop contingency plans to mitigate potential issues such as hardware failures, network bottlenecks, and software incompatibilities. + Maintain ongoing, transparent communication with all relevant stakeholders, providing updates on project status and addressing any issues or changes in scope. **Knowledge Transfer and Documentation** : + Develop and deliver detailed documentation for each deployment, covering installation procedures, system configurations, and validation reports, ensuring operational teams have clear guidance on managing the deployed systems. + Conduct post-deployment knowledge transfer sessions to educate client teams on managing AI infrastructure, troubleshooting common issues, and optimizing AI models. + Provide comprehensive training sessions on the operation, management, and scaling of AI systems, ensuring that customers are fully prepared for ongoing operations post-handoff. **Qualifications** : **Educational Background:** · Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience in AI infrastructure deployment. **Experience** : + Minimum 5+ years of experience in deploying AI/ML models using Nvidia GPUs in enterprise production environments. + Demonstrated success in leading and managing complex AI infrastructure projects, including PoC transitions to production at scale. **Technical Expertise:** + Extensive experience with Nvidia AI Enterprise, GPU-accelerated workloads, and AI/ML frameworks such as PyTorch and TensorFlow. + Proficient in deploying AI solutions across enterprise platforms, including VMware ESXi, Docker, Kubernetes, and Linux (Ubuntu/RHEL) and Windows Server environments. + MLOps proficiency with hands-on experience using tools such as Kubeflow, MLflow, or AWS SageMaker for managing the AI model lifecycle in production. + Strong understanding of virtualization and containerization technologies to ensure robust and scalable deployments. **Additional Locations** : * Malaysia * Malaysia