NVIDIA Hiring 2026 | System Software Engineer – Local AI | Pune | 2+ Years Experience | Apply Now

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NVIDIA Hiring – System Software Engineer – Local AI Opportunity

NVIDIA is hiring for the position of System Software Engineer – Local AI in Pune, Maharashtra, India. This is a full-time engineering opportunity for professionals with 2+ years of relevant experience and strong expertise in C++, machine learning, AI inference, inference runtimes, GPU programming, and performance optimization.

About NVIDIA

NVIDIA is a technology company known for developing accelerated computing platforms, GPUs, AI technologies, software, and computing solutions. NVIDIA's technologies are widely used across artificial intelligence, deep learning, data centers, gaming, professional visualization, robotics, and high-performance computing.

Job Details

Company: NVIDIA
Position: System Software Engineer – Local AI
Location: Pune, Maharashtra, India
Job Type: Full Time
Experience: 2+ Years
Category: Engineering
Job Requisition ID: JR2024810
Salary: Not Disclosed
Application Mode: Online

Eligibility Criteria

Minimum 2+ years of relevant experience.
Bachelor's, Master's, or PhD in Computer Science, Software Engineering, Mathematics, or a related field, or equivalent experience.
Excellent C++ programming and debugging skills.
Strong understanding of data structures, algorithms, and machine learning.
Experience with AI inference pipelines and ML/DL frameworks.
Understanding of inference backends and runtime internals.
Strong analytical and problem-solving skills.
Ability to work effectively in a dynamic environment and multitask.
Strong written and verbal communication skills.

Job Description

As a System Software Engineer – Local AI, you will work on technologies that enable high-performance AI inference and local or on-device AI experiences. The role involves working with inference pipelines, runtime internals, scheduling, memory management, graph execution, optimization techniques, and hardware-aware AI acceleration.

Key Responsibilities

Develop and optimize system software for local and on-device AI.
Work on AI inference pipelines and inference runtimes.
Develop and debug high-performance software using C++.
Work with inference backends and runtime internals.
Optimize scheduling, memory management, KV-cache, and graph execution.
Work on AI model optimization techniques including quantization, pruning, sparsity, and knowledge distillation.
Perform hardware-aware optimization for AI workloads.
Analyze performance and accuracy of AI inference systems.
Perform system-level debugging and performance optimization.
Work with GPU programming technologies and accelerated computing frameworks.
Contribute to open-source development and inference technologies.
Collaborate with distributed engineering teams to deliver end-to-end products.

Key Skills Required

C++
Data Structures & Algorithms
Machine Learning
Deep Learning
Generative AI
AI Inference
Local / On-Device AI
AI Inference Pipelines
Llama.cpp
vLLM
PyTorch
WinML
DXCGC
TensorRT / TensorRT-RTX
Inference Runtimes
Runtime Internals
Scheduling
Memory Management
KV-Cache
Graph Execution
Quantization
Pruning
Sparsity
Knowledge Distillation
Hardware-Aware Optimization
System-Level Debugging
Performance Optimization
GPU Programming
CUDA
Vulkan
DirectX
Performance & Accuracy Analysis
Open-Source Development
Problem Solving

Preferred / Bonus Skills

Knowledge of modern Machine Learning, Deep Neural Networks, and Generative AI.
Contributions to major open-source projects.
CUDA and low-level system/GPU programming experience.
Experience building high-performance systems.
Contributions to open-source inference runtimes, model tooling, or performance infrastructure.
Experience with Llama.cpp, PyTorch, TensorRT, Vulkan, DirectX, or vLLM.
Experience delivering end-to-end products with distributed teams.

Selection Process

The selection rounds are not specified in the job posting. Candidates should refer to the official NVIDIA careers page for the latest recruitment process and interview details.

Why Apply for This Role?

Opportunity to work on cutting-edge Local and On-Device AI technologies.
Work with AI inference pipelines and high-performance inference runtimes.
Opportunity to work with C++, CUDA, GPU programming, and system-level optimization.
Exposure to Generative AI, Deep Learning, and modern ML technologies.
Work with technologies such as TensorRT, PyTorch, vLLM, Llama.cpp, Vulkan, and DirectX.
Opportunity to contribute to open-source AI infrastructure and performance technologies.
Work with distributed engineering teams on end-to-end products.

Who Should Apply?

This opportunity is suitable for experienced software engineers with 2+ years of experience and strong C++ programming skills who are interested in AI inference, Local AI, Generative AI, machine learning, GPU programming, inference runtimes, and high-performance systems.

How to Apply?

Click on the official NVIDIA application link below.
Review the complete job requirements and responsibilities.
Check your eligibility and required technical skills.
Prepare an updated resume highlighting relevant C++, AI, ML, GPU, and systems experience.
Complete the online application with accurate information.
Submit your application and monitor your registered email for further communication.

👉 Apply Now: NVIDIA System Software Engineer – Local AI – Official Application

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Disclaimer

This job information is shared for educational and informational purposes. Job availability, eligibility requirements, location, responsibilities, salary, and recruitment processes may change at any time. Candidates are advised to verify all details on the official NVIDIA careers website before applying. Hima_Hire is not responsible for any changes made by the hiring company or for the outcome of any application.

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NVIDIA Hiring 2026 | System Software Engineer – Local AI | Pune | 2+ Years | Apply Now

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NVIDIA Hiring 2026 for System Software Engineer – Local AI in Pune. Candidates with 2+ years of experience and skills in C++, AI inference, ML, CUDA, TensorRT, PyTorch and GPU programming can apply.

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