Engineering Manager, Deep Learning Inference

Experteer Overview As Manager, Deep Learning Inference Software, you lead a world-class team advancing AI model deployment on NVIDIA GPUs. You shape and execute the inference software strategy, partnering across compiler, libraries, and research groups to optimize end-to-end pipelines. You drive performance tuning for large-scale models and guide adoption of CUDA, Triton, CUTLASS, and multi-GPU techniques. This role blends technical leadership with strategic roadmap responsibilities, impacting real-time inference at datacenter and edge scales. Compensation / Benefits * Lead and mentor a high-performing engineering team focused on deep learning inference and GPU-accelerated software. * Set strategy, roadmap, and delivery for NVIDIA’s inference frameworks engineering, with emphasis on Client AI. * Collaborate with internal compiler, libraries, and research teams to deliver end-to-end optimized inference pipelines across NVIDIA accelerators. * Oversee performance tuning, profiling, and optimization for large-scale LLM, multimodal, and generative AI workloads. * Guide engineers on CUDA, Triton, CUTLASS, and multi-GPU communications (NIXL, NCCL, NVSHMEM). * Represent the team in roadmap and planning discussions to align with broader AI and software strategies. * Foster a culture of technical excellence, collaboration, and continuous innovation. Tasks * 6+ years of software development experience; 3+ years in technical leadership or engineering management. * Strong background in C/C++ software design; Python is a plus. * Hands-on GPU programming experience (CUDA, Triton, CUTLASS) and performance optimization. * Proven record of deploying or optimizing deep learning models in production environments. * Experience leading teams using Agile or collaborative software development practices. Key requirements * equity * comprehensive benefits package * base salary and variable compensation * hybrid/remote options * career advancement opportunities

world-class for large-scale LLM, multimodal, and generative AI workloads. * Guide engineers on CUDA, Triton, CUTLASS, and multi-GPU communications (NIXL, NCCL, NVSHMEM). * Represent the team in roadmap and planning discussions to align with broader AI and software strategies. * Foster a culture of technical excellence, collaboration, and continuous innovation. Tasks * 6+ years of software development experience; 3+ years in technical leadership or engineering management. * Strong background in C/C++ software design; Python is a plus. * Hands-on GPU programming experience (CUDA, Triton, CUTLASS) and performance optimization. * Proven record of deploying or optimizing deep learning models in production environments. * Experience leading teams using Agile or collaborative software development practices. Key requirements * equity * comprehensive benefits package * base salary and variable compensation * hybrid/remote options * career advancement opportunities