NVIDIA

2 days ago

Senior System Software Engineer - 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

Build and optimize NVIDIA’s local AI inference stack for RTX, RTX Pro, and DGX-class GPUs, focusing on high performance, stability, and scalability. Develop modern inference runtimes and execution stacks spanning frameworks such as Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT-RTX. Own end-to-end optimization of models, data pipelines, and runtimes, including quantization, pruning, sparsity, and distillation, and drive production-ready bring-up through debugging and performance analysis.

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Partner with NVIDIA software, research, architecture, and product teams to align strategies and technical needs for the AI ecosystem on RTX and DGX PCs.
•Build and optimize local AI inference stack for RTX, RTX Pro, and DGX GPUs across hardware architectures.
•Design and develop modern inference runtimes and execution stacks across LLM, vision-language, TTS, ASR, and diffusion AI workloads.
•Perform end-to-end optimization of AI models, data pipelines, and inference runtimes, applying quantization, pruning, sparsity, and distillation for efficient deployment.
•Conduct system-level debugging and performance–accuracy trade-off analysis, establish engineering guidelines for bring-up, and ensure production readiness of new inference backends.

Key Requirements

•5+ years of experience with a 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 strong understanding of data structures, algorithms, and machine learning.
•Proven experience with AI inferencing pipelines and applications using ML/DL frameworks such as Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT.
•Deep interest in inference backends and runtime internals, including scheduling, memory management, KV-cache behavior, graph execution, quantization, and hardware-aware optimization.
•Strong analytical and problem-solving abilities, plus strong written and oral communication skills for collaboration.

Experience:5+ yearsAIMLDeep learningGenerative AIOpen source

Education:

Skills:DebuggingAnalytical thinkingProblem-solvingCommunicationCollaborationMultitasking

Tech Stack:C++Llama.cppVLLMPyTorchWinMLDXCGCTensorRT-RTXTensorRTCUDAVulkanDirectXRTXDGX

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

Senior System Software Engineer - 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: Mid level

Key Responsibilities

•Partner with NVIDIA software, research, architecture, and product teams to align strategies and technical needs for the AI ecosystem on RTX and DGX PCs.
•Build and optimize local AI inference stack for RTX, RTX Pro, and DGX GPUs across hardware architectures.
•Design and develop modern inference runtimes and execution stacks across LLM, vision-language, TTS, ASR, and diffusion AI workloads.
•Perform end-to-end optimization of AI models, data pipelines, and inference runtimes, applying quantization, pruning, sparsity, and distillation for efficient deployment.
•Conduct system-level debugging and performance–accuracy trade-off analysis, establish engineering guidelines for bring-up, and ensure production readiness of new inference backends.

Key Requirements

•5+ years of experience with a 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 strong understanding of data structures, algorithms, and machine learning.
•Proven experience with AI inferencing pipelines and applications using ML/DL frameworks such as Llama.cpp, vLLM, PyTorch, WinML, DXCGC, and TensorRT.
•Deep interest in inference backends and runtime internals, including scheduling, memory management, KV-cache behavior, graph execution, quantization, and hardware-aware optimization.
•Strong analytical and problem-solving abilities, plus strong written and oral communication skills for collaboration.

Experience:5+ yearsAIMLDeep learningGenerative AIOpen source

Education:

Skills:DebuggingAnalytical thinkingProblem-solvingCommunicationCollaborationMultitasking

Tech Stack:C++Llama.cppVLLMPyTorchWinMLDXCGCTensorRT-RTXTensorRTCUDAVulkanDirectXRTXDGX

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