Senior System Software Engineer - Local AI

Responsibilities

• Partner with NVIDIA's software, research, architecture, and product leadership, as well as external partners such as Microsoft, to align technical requirements and strategic priorities, fostering the AI ecosystem on RTX and DGX PCs.
• Build and optimize the local AI inference stack for RTX, RTX Pro, and DGX GPUs, with a focus on performance, stability, and scalability across diverse hardware architectures.
• Architect and develop modern inference runtimes and execution stacks using frameworks such as llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT-RTX, supporting LLM, vision-language, TTS, ASR, and diffusion-based AI workloads.
• Perform end-to-end optimization of AI models, data pipelines, and inference runtimes to maximize performance on current and next-generation GPU architectures. Apply model optimization techniques, including quantization, pruning, sparsity, and distillation, to enable efficient deployment of large models on local and…
• Lead system-level debugging, performance tuning, and performance-accuracy trade-off analysis; develop infrastructure for performance and accuracy sweeps; analyse results to identify gaps and drive fixes; and establish engineering guidelines to accelerate bring-up and ensure production readiness of new models and…
• Mentor other engineers and review architecture proposals spanning several groups, acting as a force multiplier for technical quality and consistency across the broader LocalAI organization.
• What we need to see
• 5+ Years of experience with Bachelor’s, Master’s, or PhD in Computer Science, Software Engineering, Mathematics, or related field, or equivalent experience.
• Excellent C++ programming and debugging skills, with a strong foundation in data structures, algorithms, and machine learning.
• Proven experience architecting and optimizing AI inference pipelines and applications using ML/DL frameworks such as Llama.cpp, vLLM, PyTorch, Windows ML, DXCGC, and TensorRT.

Languages