Manager, System Software Engineering - Local AI

Lead and grow a team building the on-device AI inference platform for RTX, RTX Pro, and DGX GPUs, with accountability for execution, technical direction, delivery quality, and roadmap alignment.

Drive cross-functional alignment with NVIDIA’s software, research, architecture, and product teams, along with industry partners and open-source communities, to build strategy and strengthen the AI ecosystem across RTX and DGX platforms.

Provide technical leadership for the architecture and evolution of modern inference runtimes and execution stacks across frameworks such as Llama.cpp, vLLM , PyTorch , WinML , DXCGC, and TensorRT-RTX, spanning workloads including LLMs, vision-language models, TTS, ASR, and diffusion models.

Mentor engineers, develop technical leaders, and foster a high-perfor man ce team culture centred on innovation, collaboration, and operational excellence.

Coordinate end-to-end optimization of AI models, data pipelines, and inference runtimes to improve perfor man ce across current and next-generation GPU architectures.

Drive adoption of model optimization techniques such as quantization, pruning, sparsity, and distillation to enable efficient deployment of large models on local and edge devices.

Establish team processes for system-level debugging, perfor man ce optimization, and perfor man ce-accuracy trade-off analysis, including infrastructure for perfor man ce and accuracy sweeps, gap analysis, and production-readiness improvements.

5+ overall years of industry experience and 2+ years of engineering leadership experience, combined with a Bachelor’s, Master’s, or PhD in Computer Science, Software Engineering, Mathematics, or a related field.

Proven experience leading high-performing engineering teams in systems software, AI infrastructure, inference runtimes, or related domains.

Strong technical foundation in C++ software development, debugging, data structures, algorithms, and machine learning systems.