NVIDIA is seeking a Software Engineering Manager to lead a team developing advanced network simulation and testing software for next-generation AI and Machine Learning infrastructure.
In this role, you will lead the development of tools and frameworks used to simulate, validate, and test networking environments at scale. These solutions play a critical role in ensuring the reliability, performance, and scalability of NVIDIA networking technologies powering cutting-edge ML and datacenter platforms.
You will work closely with software, networking, QA, and infrastructure teams to deliver robust simulation and automation capabilities in highly complex environments. This position offers the opportunity to contribute to technologies shaping the future of AI infrastructure within a fast-paced and innovative organization.
What You’ll Be Doing:
Lead and manage a team of software engineers developing network simulation and testing solutions
Drive the design and development of scalable simulation environments and automated testing frameworks
Collaborate with networking, software, QA, and infrastructure teams to validate next-generation networking technologies
Support development and debugging activities across complex simulated environments
Improve development workflows, CI/CD processes, automation, and software quality practices
Mentor engineers and foster a strong technical and collaborative team culture
Contribute to technical decision-making, prioritization, and execution planning
Bachelor’s degree in Computer Science, Electrical Engineering, or equivalent practical experience
8+ overall years of software industry experience, including 3+ years of experience in leading or managing engineering teams
Strong programming experience in Python and/or C/C++
Experience developing automation, simulation, or testing frameworks
Experience with Linux development environments
Familiarity with DevOps methodologies, CI/CD pipelines, and automation tools
Strong debugging, problem-solving, and analytical skills
Ability to learn quickly and work effectively in a fast-paced environment
Strong communication and collaboration skills
Experience with networking technologies and protocols
Experience building simulation environments or large-scale automated test systems
Familiarity with containerized environments and orchestration technologies
Experience with infrastructure automation and monitoring tools
Background in AI/ML infrastructure, datacenter technologies, or distributed systems
Skills Required
- Bachelor's degree in Computer Science, Electrical Engineering, or equivalent practical experience
- 8+ years of software industry experience
- 3+ years of experience in leading or managing engineering teams
- Strong programming experience in Python and/or C/C++
- Experience developing automation, simulation, or testing frameworks
- Experience with Linux development environments
- Familiarity with DevOps methodologies, CI/CD pipelines, and automation tools
- Strong debugging, problem-solving, and analytical skills
- Ability to learn quickly and work effectively in a fast-paced environment
- Strong communication and collaboration skills
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
