NVIDIA
Technology
SeniorSystemSoftwareEngineer-WindowsDevOpsandTestLabs
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“Senior System Software Engineer - Windows DevOps and Test Labs at NVIDIA. Skills: Windows AI Automation, DevOps, Infrastructure development, AI workloads. Develop reliable infrastructure. Deploy reliable infrastructure”
Industry & Context.
Problem-solving abilities; Debug issues; Identify performance bottlenecks; Devise solutions
What They're Looking For.
Must Have
B. Tech or higher degree, 5+ years of experience, 4 years of proficiency in application development using C#, Java, or another programming language, Exposure to at least one scripting language such as Python, Perl, or PHP, Familiarity with databases and SQL, Experience working with source control systems, Experience with CI/CD pipelines
Nice to Have
Experience building backend automation systems, Practical involvement working with databases, Familiarized in setting up visualization interfaces, Confirmed background working with Git, Confirmed background working with Jenkins CICD pipelines, Hands on experience with inference frameworks
What You'll Do.
Develop reliable infrastructure
Deploy reliable infrastructure
Sustain reliable infrastructure
Scope requirements for deploying AI applications
Scope requirements for deploying benchmarks
Scope requirements for deploying models
Develop solutions to measure accuracy
Develop solutions to measure functionality
Develop solutions to measure performance
Develop infrastructure to download AI models
Handle a local repository
Create automated synchronization mechanism
Analyze large datasets
Design visualizations
Implement data processing engines
Collaborate with developers
Implement features in automation
Debug issues in current frameworks
Identify performance bottlenecks
Devise solutions to enhance efficiency
Build continuous integration workflows
Implement continuous integration workflows
Maintain continuous integration workflows
Build continuous delivery workflows
Implement continuous delivery workflows
Maintain continuous delivery workflows
How You'll Work.
Team & Collaboration
Collaborate with internal WinAI developers; Collaborate with management; Collaborate with engineering teams
Communication Scope
Written communication; Oral communication
Process & Methodology
CI/CD pipelines
Full Job Description
NVIDIA is a pioneering company that revolutionized the computing world with its GPU technology, driving the growth of the PC gaming market and redefining modern computer graphics. With the recent advancement of GPU deep learning has ushered AI into a new era of computing, positioning GPUs as the driving force behind intelligent applications in productivity, gaming, and creative fields, solidifying NVIDIA's position as the leading "AI computing company." There is a growing emphasis on processing AI computations at the edge, closer to the source of data. This approach reduces latency, enhances real-time processing, and addresses privacy concerns by minimizing the need for sending data to centralized servers. As technology continues to advance, we can expect client-side AI (local execution) to play a pivotal role in shaping the digital landscape. The Windows AI Automation team is seeking a senior software engineer passionate about building and maintaining robust infrastructure for deploying high-quality AI applications and models. You will collaborate with a team of highly qualified engineers dedicated to creating top-tier infrastructure for Windows AI automation. If you have a real passion for setting up automation systems in the Windows AI ecosystem to achieve excellence, this could be an excellent opportunity for us to work together! **What you 'll be doing:** * Develop, deploy, and sustain reliable infrastructure to efficiently run various AI workloads through different inference backends like WinML, Direct ML, TRT-RTX, and others. * Scope out the requirements for deploying various AI applications, benchmarks and models in automation, and develop solutions to measure accuracy, functionality and performance. * Develop Infrastructure to download AI models from various sources and efficiently handle a local repository, create an automated synchronization mechanism to keep repository up to date. * Analyze large datasets to derive insights and design visualizations, imp
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