LLM Engineer

• Lead end-to-end deployment of GPU clusters, storage systems, and networking fabric across Lambda’s data centers.
• Design and implement data center network topologies optimized for AI and HPC workloads, including high-speed Ethernet and InfiniBand environments.
• Oversee rack implementation, cabling, and power/cooling validation for optimal efficiency and scalability.
• Collaborate with supply chain, logistics, and operations teams to ensure smooth delivery and installation timelines.
• Implement Layer 2/Layer 3 networks, including VLANs, Spine to Leaf architecture, Infiniband interconnect technology.
• Partner with network architects to ensure redundancy, scalability, and low-latency interconnects for distributed AI workloads.
• Monitor network health, identify bottlenecks, and implement optimizations to maintain peak performance.
• Oversee server hardware troubleshooting, including GPUs, NICs, CPUs, and storage components.
• Lead root-cause analysis for system issues and drive corrective actions in collaboration with vendors and internal hardware teams.
• Develop standard operating procedures (SOPs) for hardware validation, deployment, and maintenance.
• Serve as technical project lead for infrastructure rollouts and cluster expansion projects.
• Coordinate cross-functional teams — networking, facilities, cloud operations, and hardware engineering — to execute deployments on schedule.
• Manage project scope, budgets, risk assessments, and post-deployment reviews.
• Communicate status, challenges, and milestones to leadership with clarity and precision.
• Maintain detailed network topology diagrams, deployment runbooks, and hardware inventories.
• Identify opportunities for process automation and infrastructure standardization across deployments.
• Contribute to Lambda’s internal knowledge base and mentor junior engineers on data center best practices.

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