NVIDIA

2 days ago

Manager, System Software Engineering - Local AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Lead a team building NVIDIA’s on-device AI inference platform for RTX, RTX Pro, and DGX systems. Own execution, technical direction, delivery quality, and roadmap alignment while driving cross-functional collaboration across software, research, architecture, and product. Provide technical leadership for inference runtimes and execution stacks across frameworks like Llama.cpp, vLLM, PyTorch, WinML, and TensorRT, and coordinate model/data pipeline optimizations for low-latency, efficient, scalable local AI deployment.

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Manager level

Key Responsibilities

•Lead and grow a team building the on-device AI inference platform for RTX, RTX Pro, and DGX GPUs, owning execution, technical direction, delivery quality, and roadmap alignment.
•Drive cross-functional alignment across NVIDIA software, research, architecture, and product teams, plus industry partners and open-source communities, to strengthen the AI ecosystem across RTX and DGX.
•Provide technical leadership for the architecture and evolution of modern inference runtimes and execution stacks across frameworks including Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT-RTX.
•Mentor engineers, develop technical leaders, and foster a high-performance team culture focused on innovation, collaboration, and operational excellence.
•Coordinate end-to-end optimization of AI models, data pipelines, and inference runtimes, including adoption of quantization, pruning, sparsity, and distillation for deployment on resource-constrained platforms.

Key Requirements

•5+ years of industry experience and 2+ years of engineering leadership experience, 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++ development, debugging, data structures, algorithms, and machine learning systems.
•Extensive background in AI inference pipelines and deep learning frameworks such as Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT.
•Deep understanding of inference backends and runtime internals (e.g., scheduling, memory management, KV-cache behavior, graph execution, quantization, hardware-aware optimization).

Experience:5+ yearsAI infrastructureInference runtimesDeep learningLocal AIOn-device AI

Education:

Skills:LeadershipTechnical mentoringCommunicationCollaborationProblem-solving

Tech Stack:C++Llama.cppVLLMPyTorchWinMLDXCGCTensorRTTensorRT-RTXCUDAVulkanDirectX

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

2 days ago

Manager, System Software Engineering - Local AI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Manager level

Key Responsibilities

•Lead and grow a team building the on-device AI inference platform for RTX, RTX Pro, and DGX GPUs, owning execution, technical direction, delivery quality, and roadmap alignment.
•Drive cross-functional alignment across NVIDIA software, research, architecture, and product teams, plus industry partners and open-source communities, to strengthen the AI ecosystem across RTX and DGX.
•Provide technical leadership for the architecture and evolution of modern inference runtimes and execution stacks across frameworks including Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT-RTX.
•Mentor engineers, develop technical leaders, and foster a high-performance team culture focused on innovation, collaboration, and operational excellence.
•Coordinate end-to-end optimization of AI models, data pipelines, and inference runtimes, including adoption of quantization, pruning, sparsity, and distillation for deployment on resource-constrained platforms.

Key Requirements

•5+ years of industry experience and 2+ years of engineering leadership experience, 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++ development, debugging, data structures, algorithms, and machine learning systems.
•Extensive background in AI inference pipelines and deep learning frameworks such as Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT.
•Deep understanding of inference backends and runtime internals (e.g., scheduling, memory management, KV-cache behavior, graph execution, quantization, hardware-aware optimization).

Experience:5+ yearsAI infrastructureInference runtimesDeep learningLocal AIOn-device AI

Education:

Skills:LeadershipTechnical mentoringCommunicationCollaborationProblem-solving

Tech Stack:C++Llama.cppVLLMPyTorchWinMLDXCGCTensorRTTensorRT-RTXCUDAVulkanDirectX

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor