Software Engineer, CUDA-Q Libraries

Reposted 10 Days Ago
Be an Early Applicant
4 Locations
Remote
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop CUDA-Q platform for hybrid quantum-classical systems, focusing on AI algorithms, real-time interfaces, and performance optimization.
Summary Generated by Built In

NVIDIA's Quantum Computing team is searching for an outstanding software engineer to build the toolchain of the future. Join us in developing the CUDA-Q platform for programming powerful hybrid quantum-classical multi-processor systems. We are looking for a dedicated engineer with expertise in real-time systems, GPU-programming, and is proficient in parallel and distributed programming. Are you creative, always looking to come up with innovative solutions, and eager to apply your skills to advance a novel field of computing? If you love the craft of software engineering and high-performance algorithm implementation, and relish the chance to impact the future of the industry, this role may be perfect for you.

What You'll Be Doing:

  • Identifying and productizing AI and algorithmic real-time decoding algorithms in collaboration with NVIDIA's Applied Research team

  • Contributing to the development of CUDA Quantum libraries by building AI training infrastructure for the CUDA-Q Quantum Error Correction (QEC) library

  • Developing real-time hardware and software interfaces for the heterogenous quantum/classical computing enabled by CUDA Quantum

  • Solving difficult problems at the intersection of HPC and quantum computing to enable ground-breaking research and technology

  • Improving processes and infrastructure to accelerate our development

What We Need To See:

  • Bachelors Degree (or equivalent experience) in Computer Science, Physics or related engineering field with 8+ years of relevant work experience; Ph.D. or Masters preferred.

  • C/C++ proficiency is required

  • Proficiency in algorithm analysis and implementation on heterogenous systems including CPUs, GPUs, and FPGAs.

  • Ability to quickly develop expertise in new domains and products, and eagerness to master new challenges

  • Experience building performant and robust production software on large-scale hardware and software projects

  • Strong communication and collaboration skills

Ways To Stand Out From The Crowd:

  • Experience with quantum computing hardware and control systems

  • Domain knowledge of Quantum Error Correction and/or prior experience implementing decoding algorithms

  • A demonstrated history of software optimizations of real-time systems and a focus on improving extensibility

NVIDIA is widely considered to be one of high technology's most desirable employers. Our inventions have revolutionized parallel computing and our GPUs are being used in many of the largest high-performance computing projects around the world. We have some of the most forward-thinking and experienced people in the world working for us. Our goal is to create an environment where we can do our life's best work. If you're creative, autonomous, and highly motivated, we want to hear from you!

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 September 9, 2025.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Algorithms
C++
Distributed Programming
Gpu Programming
Parallel Programming
Quantum Computing
Real-Time Systems
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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