Senior AI Performance and Efficiency Engineer
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The role
Lead efforts to improve AI/ML model efficiency on GPU clusters, delivering productivity gains and substantial cost savings for researchers.
Build tools, frameworks, and apply ML techniques to detect, analyze, and mitigate efficiency bottlenecks across workloads.
Collaborate with researchers across Robotics, Autonomous Vehicles, LLMs, and video workloads to optimize diverse AI workloads.
Partner with hardware, software, and infrastructure teams to improve utilization, scalability, and end-to-end performance.
Profile, debug, and optimize training and inference end-to-end using Nsight Systems/Compute and NCCL for distributed training.
Stay current with AI/ML infrastructure developments and advocate for adopting new techniques to advance research capabilities.
Build tools, frameworks, and apply ML techniques to detect, analyze, and mitigate efficiency bottlenecks across workloads.
Collaborate with researchers across Robotics, Autonomous Vehicles, LLMs, and video workloads to optimize diverse AI workloads.
Partner with hardware, software, and infrastructure teams to improve utilization, scalability, and end-to-end performance.
Profile, debug, and optimize training and inference end-to-end using Nsight Systems/Compute and NCCL for distributed training.
Stay current with AI/ML infrastructure developments and advocate for adopting new techniques to advance research capabilities.
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