NVIDIA Corporation

Senior Software Engineer, Quantum Applied Research

NVIDIA Corporation$184K — $356K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • BS, MS, or PhD in Computer Science, Engineering, Physics or equivalent experience.
  • 10+ years of experience in production-grade software systems, with a focus on data engineering and distributed systems.
  • Working knowledge of quantum computing concepts for collaboration with domain experts.
  • Hands-on experience with backend technologies (Python, C++, Go, APIs, distributed services).
  • Strong practices in software engineering including testing, CI/CD, and performance optimization.

Responsibilities

  • Build and evolve scalable data platforms to integrate diverse system data and application workflows.
  • Design and implement agentic orchestration frameworks for modeling and prediction across computing systems.
  • Develop synthetic data generation pipelines for AI model training and validation.
  • Implement robust data pipelines, storage systems, and APIs for high-throughput workloads.
  • Collaborate with research and engineering teams to translate complex models into reliable systems.

Benefits

  • Equity compensation as part of the overall rewards package.
  • Access to cutting-edge technologies and working on advanced applications in AI and physics.
  • Dynamic work environment that encourages interdisciplinary collaboration.
  • Opportunities for professional growth with a focus on innovation and development.
Full Job Description
As a Senior Software Engineer, you will design and build data interfaces, orchestration layers, and system foundations that connect applications, simulation environments, AI models, and emerging computing systems. You will develop scalable data architectures, synthetic data generation pipelines, and agentic systems that enable advanced prediction, analysis, and co-design across complex systems. You will collaborate across Product, Engineering, and Applied Research to explore new platform capabilities for accelerated computing. Do you enjoy building new system abstractions, working across disciplines, and operating at the frontier of software, AI, and physics? If yes, we would love to hear from you!

What you'll be doing:
  • Build and evolve scalable data platforms and interfaces that integrate heterogeneous system data, simulation outputs, AI model inputs/outputs, and application workflows.
  • Design and implement agentic orchestration frameworks to support modeling, prediction, and coordination across complex computing systems.
  • Develop synthetic data generation pipelines and supporting infrastructure for training, validation, and evaluation of AI-driven models.
  • Implement robust data pipelines, storage systems, and APIs to support high-throughput, low-latency workloads across simulation and real-time environments.
  • Collaborate closely with research and engineering teams to translate domain-specific models and system signals into performant, reliable systems.


What we need to see:
  • BS, MS, or PhD in Computer Science, Engineering, Physics, or a related field (or equivalent experience).
  • 10+ years of experience building and operating production-grade software systems, with strong fundamentals in data engineering and distributed systems.
  • Working knowledge of quantum computing concepts and the ability to collaborate effectively with domain experts.
  • Hands-on experience with backend and data technologies (e.g., Python, C++, Go, APIs, distributed services, and modern data platforms).
  • Strong software engineering practices across testing, CI/CD, observability, and performance optimization.


Ways to stand out from the crowd:
  • Experience building simulation or modeling platforms in scientific computing, physics, or hardware-software environments.
  • Experience developing synthetic data pipelines or supporting AI/ML workflows at scale.
  • Familiarity with agentic systems, orchestration frameworks, or AI-driven automation.
  • Deeper exposure to quantum computing concepts, including hardware, control systems, or performance modeling.
  • Experience with GPU acceleration, CUDA, or high-performance computing for large-scale workloads.


Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 4, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ

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