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Internship Ibm Quantum Machine Learning Jobs (NOW HIRING)

Nvidia

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$15 - $20/hr

Integrating various classical machine learning methods for identifying high-performance code ... Our internship hourly rates are a standard pay based on the position, your location, year in school ...

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Machine Learning Intern

Mountain View, CA · Hybrid

$40/hr

This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program ... of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large ...

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How much do internship ibm quantum machine learning jobs pay per year?

As of May 28, 2026, the average yearly pay for internship ibm quantum machine learning 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 are the key skills and qualifications needed to thrive as an IBM Quantum Machine Learning Intern, and why are they important?

To excel as an IBM Quantum Machine Learning Intern, you typically need a background in computer science, physics, or a related field, with strong programming skills (Python) and foundational knowledge in quantum computing and machine learning. Familiarity with quantum programming frameworks such as Qiskit, as well as experience with machine learning libraries like TensorFlow or PyTorch, is highly beneficial. Strong analytical thinking, problem-solving abilities, and effective communication skills distinguish top candidates in this role. These competencies enable interns to contribute meaningfully to research projects, collaborate with interdisciplinary teams, and adapt to rapidly evolving technologies in quantum computing.

What kinds of projects or tasks can interns expect to work on during an IBM Quantum Machine Learning internship?

During an IBM Quantum Machine Learning internship, interns often collaborate with research scientists and engineers on projects that explore the intersection of quantum computing and machine learning. Typical responsibilities include implementing quantum algorithms, analyzing experimental data, developing proof-of-concept applications, and contributing to open-source software or research publications. Interns may also participate in team meetings, technical discussions, and code reviews, gaining exposure to cutting-edge quantum technologies and professional research environments. This hands-on experience provides valuable insight into both academic and industry applications of quantum machine learning.

What is an IBM Quantum Machine Learning Internship?

An IBM Quantum Machine Learning Internship is a temporary position for students or recent graduates to work alongside IBM researchers and engineers on projects at the intersection of quantum computing and machine learning. Interns typically contribute to developing algorithms, running experiments on real quantum hardware, and advancing the understanding of how quantum computers can enhance machine learning tasks. The internship provides hands-on experience with IBM's quantum technologies, including Qiskit, and offers opportunities to collaborate with leading experts in the field. Applicants generally need a background in computer science, physics, mathematics, or related fields, and some familiarity with quantum computing concepts.

What is the difference between Internship Ibm Quantum Machine Learning vs Data Science Intern?

AspectInternship Ibm Quantum Machine LearningData Science Intern
Required CredentialsBasic knowledge of quantum computing, programming, and machine learningBackground in statistics, programming, and data analysis
Work EnvironmentResearch-focused, technology-driven, often in labs or R&D teamsBusiness or research settings, analyzing large datasets
Industry UsageEmerging field within tech and research sectorsWidely used across industries like finance, healthcare, and tech
Search & Comparison IntentUnderstanding quantum ML internship opportunitiesExploring data science internship roles

Internship Ibm Quantum Machine Learning focuses on applying quantum computing techniques to machine learning problems, often requiring knowledge of quantum algorithms and programming. In contrast, Data Science Internships involve analyzing data, building models, and deriving insights using traditional data analysis tools. Both roles are research-oriented but differ in technical focus and industry application.

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Internship Ibm Quantum Machine Learning jobs near you
Quantum Calibrations Intern, Quantum Computing Services

Quantum Calibrations Intern, Quantum Computing Services

QuEra Computing, Inc.

Boston, MA • On-site

$16.25 - $21.75/hr

Full-time, Internship

Posted 8 days ago

Job description

Job Title: Intern, Quantum Calibrations, Quantum Computing Services
Job Type: Full-time, 3-6 months
Job Location: Boston, MA
Reports to: VP of Quantum Computing Services
Summary:
QuEra is seeking motivated interns to join our growing team focused on developing the calibration and performance characterization framework for QuEra's neutral-atom quantum computers. As an intern, you will collaborate with physicists, software engineers, and hardware specialists to design benchmarking protocols, build physics-informed models of device behavior, and develop predictive tools for real-time qubit state evolution.
This internship offers a unique opportunity to gain hands-on experience at the interface of quantum hardware and data science, contributing to the development of calibration and performance characterization frameworks for scalable, reliable neutral-atom quantum computers.
This role is part of QuEra's Quantum Computing Services team and is based at QuEra's Boston headquarters. The team's mission is to develop QuEra's neutral-atom technology into cutting-edge quantum computing products and services.
Core Responsibilities
  • Develop and test data analysis routines to fit, visualize, and interpret experimental data.
  • Design and execute device benchmarking and characterization experiments.
  • Build and apply Hamiltonian learning routines to infer effective system parameters from time-evolution data.
  • Develop predictive models for key performance metrics (gate fidelity, coherence, readout error) using time-series calibration history and machine learning methods.
  • Collaborate closely with physicists, engineers, and software developers to integrate your work into QuEra's operational stack.

Qualifications
Required
  • Foundational understanding of quantum mechanics and open quantum systems at the graduate level.
  • Experience designing and analyzing experiments involving quantum or physical systems
  • Strong programming skills in Python, including familiarity with libraries such as NumPy, SciPy, Pandas, and Matplotlib.
  • Enjoys hands-on experimentation, iteration, and uncovering structure in data.
  • Strong analytical, problem-solving, and communication skills.

Preferred
  • Familiarity with quantum gate characterization protocols (randomized benchmarking, process tomography, GST) and error budget decomposition.
  • Exposure to Hamiltonian learning, system identification, or quantum noise spectroscopy methods.
  • Experience applying machine learning (Gaussian processes, time-series models, or neural networks) to physical or experimental data.
  • Exposure to laboratory instrumentation, data acquisition, or experimental control systems.

Education & Experience
  • Currently pursuing or recently completed a Master's or PhD in Physics, Applied Physics, Computer Science, Electrical Engineering, Applied Mathematics, or a related quantitative field.

QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.

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