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Machine Learning Quantum Computing Jobs (NOW HIRING)

Umd

ARLIS Quantum Research Professional

College Park, MD

$17.75 - $24.50/hr

... intelligence / machine learning, quantum science, and human-machine teaming. Researchers ... Critically evaluating the utility of emerging quantum computing, sensing, and networking ...

EPB

Quantum Software Engineer Fellow

Chattanooga, TN

Participate in a structured curriculum focused on quantum computing and quantum algorithm ... Machine learning * Python programming language CERTIFICATIONS & OTHER REQUIREMENTS * US citizenship ...

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Machine Learning Quantum Computing information

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$25.5K

$42.6K

$88K

How much do machine learning quantum computing jobs pay per year?

As of Aug 2, 2026, the average yearly pay for machine learning quantum computing in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Quantum Computing vs Data Scientist?

AspectMachine Learning Quantum ComputingData Scientist
Required CredentialsAdvanced degrees in quantum computing, machine learning, or related fieldsDegree in data science, statistics, or computer science
Work EnvironmentResearch labs, tech companies focusing on quantum tech, academiaBusiness environments, tech companies, consulting firms
Industry UsageEmerging quantum tech industry, research institutionsFinance, healthcare, marketing, e-commerce
Common Search/ComparisonQuantum algorithms, quantum machine learningData analysis, predictive modeling

Machine Learning Quantum Computing specialists focus on developing algorithms that leverage quantum mechanics to enhance machine learning tasks, often requiring advanced knowledge of quantum physics. Data Scientists analyze and interpret large datasets using traditional machine learning techniques. While both roles involve machine learning, the former emphasizes quantum computing applications, whereas the latter centers on data analysis in conventional computing environments.

What are the key skills and qualifications needed to thrive as a Machine Learning Quantum Computing Specialist, and why are they important?

To thrive in Machine Learning Quantum Computing, you need strong foundations in quantum mechanics, linear algebra, and advanced machine learning concepts, typically supported by a degree in physics, computer science, or a related field. Familiarity with quantum programming languages (such as Qiskit or Cirq), cloud-based quantum platforms, and proficiency in Python are usually required, alongside experience with relevant certifications or coursework. Strong problem-solving skills, adaptability, and effective collaboration are vital soft skills in this interdisciplinary field. These competencies are crucial for driving innovation and bridging the gap between quantum computing and practical machine learning applications.

How do professionals in Machine Learning Quantum Computing typically collaborate with interdisciplinary teams?

Professionals in Machine Learning Quantum Computing often work closely with experts in physics, computer science, and engineering. Collaboration usually involves translating quantum concepts for machine learning specialists and vice versa, ensuring that algorithms are both theoretically sound and practically implementable on quantum hardware. Regular meetings, code reviews, and knowledge-sharing sessions are standard, as interdisciplinary insight is crucial for advancing research and developing scalable solutions. Effective communication and a willingness to learn from other domains are essential for success in these teams.

What is Machine Learning Quantum Computing?

Machine Learning Quantum Computing is an interdisciplinary field that combines principles of quantum computing with machine learning techniques. It aims to leverage the computational power of quantum computers to enhance the performance of machine learning algorithms, potentially solving complex problems more efficiently than classical computers. This area includes developing quantum algorithms for tasks such as classification, clustering, and optimization, as well as using machine learning to improve quantum hardware and error correction. Researchers expect that, as quantum hardware matures, this field could revolutionize data analysis, cryptography, and scientific discovery.
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What cities are hiring for Machine Learning Quantum Computing jobs? Cities with the most Machine Learning Quantum Computing job openings:
What states have the most Machine Learning Quantum Computing jobs? States with the most job openings for Machine Learning Quantum Computing jobs include:
What job categories do people searching Machine Learning Quantum Computing jobs look for? The top searched job categories for Machine Learning Quantum Computing jobs are:
Machine Learning Quantum Computing jobs near you
Infographic showing various Machine Learning Quantum Computing job openings in the United States as of July 2026, with employment types broken down into 83% Full Time, 15% Part Time, and 2% Contract. Highlights an 80% Physical, 3% Hybrid, and 17% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Senior Quantum Computing Libraries Engineer

Nvidia

New York, NY • Hybrid

$134K - $176K/yr

Full-time

Re-posted 10 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 241 rated software companies

Job description

NVIDIA's accelerated computing platform has revolutionized HPC and AI, and we have built the cuQuantum SDK to enable researchers and framework developers in the area of Quantum Computing. This role will be part of an engineering team developing, scaling, and optimizing software to accelerate and scale quantum computing and quantum system simulations. Ideal candidates will have experience building software systems and curiosity about advancing the state-of-the-art in applications of HPC and GPUs to the quantum computing ecosystem. If you are passionate about designing and developing high-performance software and want to help us build libraries to significantly accelerate research and development in this exciting field, we would love to hear from you!


What you'll be doing:

  • Researching and developing and optimizing GPU accelerated algorithms across multiple hardware generations

  • Develop innovative HPC algorithms to scale quantum circuit simulations

  • Working closely with NVIDIA Research, Developer Technology, and Product Management teams in the areas of quantum computing, HPC technologies, and machine learning

  • Interacting with external partners and researchers to understand their use cases and requirements

  • Providing technical leadership and guidance to other engineers

  • Analyzing the performance of GPU, CPU, multi-GPU/multi-node implementations, finding opportunities for algorithmic or implementation-based improvements


What we need to see:

  • Excellent C++ and Python programming and software design skills, including functional and performance test design

  • Experience programming for GPUs, in a multi-threading and multi-node MPI programming model, and expertise in hardware-aware optimization

  • Experience with agentic coding tools

  • Demonstrated ability developing scientific software used in quantum simulations (e.g., circuit simulators, compilers, hybrid-computing)

  • PhD or MSc degree in Computer Science, Applied Math, Physics, or related science or engineering field (or equivalent experience)

  • 8+ years of experience

  • Strong collaboration, communication, and documentation skills


Ways to stand out from the crowd:

  • Experience using one or more quantum computing and deep learning frameworks (e.g., Qiskit, Cirq, Pennylane, TNQVM, TensorFlow, PyTorch)

  • Proven experience with HPC technologies and communication algorithms

  • Expertise in numerical methods, Hamiltonian integrals, quantum simulation techniques

  • Experience working in an agile software development environment within a globally distributed organization


With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing.

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 20, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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