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Internship Ibm Quantum Machine Learning Jobs in Baltimore, MD

ARLIS Quantum Research Professional

College Park, MD ยท On-site

$17.75 - $24.50/hr

ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human ...

ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human ...

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Internship Ibm Quantum Machine Learning information

See Baltimore, MD salary details

$25.3K

$42.3K

$87.4K

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

As of Aug 25, 2026, the average yearly pay for internship ibm quantum machine learning in Baltimore, MD is $42,313.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,300.00 and $45,700.00 per year, depending on experience, location, and employer.

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 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 are the key skills and qualifications needed to thrive as an IBM Quantum Machine Learning intern?

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 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.

What are popular job titles related to Internship Ibm Quantum Machine Learning jobs in Baltimore, MD?

For Internship Ibm Quantum Machine Learning jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Internship Ibm Quantum Machine Learning jobs in Baltimore, MD look for?

The top searched job categories for Internship Ibm Quantum Machine Learning jobs in Baltimore, MD are:

Machine Learning Application Engineer

Umd

College Park, MD โ€ข On-site

Full-time

Re-posted 17 days ago


Job description

Job Description SummaryOrganization's Summary Statement:
The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland is a University-Affiliated Research Center (UARC) dedicated to advancing research, innovation, and technology transition to improve decision making for U.S. national security. ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human-machine teaming. Researchers, scientists, engineers, and analysts at ARLIS collaborate with government agencies, industry partners, and academic institutions to deliver actionable insights and transformative solutions through research and development. Employees at ARLIS work on projects of critical importance, contribute directly to the nation's security, and are supported by a culture that values integrity, collaboration, and professional growth.
The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland, College Park, is seeking qualified candidates with expertise in applied machine learning (ML) application development to build, deploy, and sustain end-to-end ML capabilities in support of U.S. national security missions. Ideal candidates will demonstrate experience translating technical problems into robust ML solutions-spanning data selection and preparation, model development, evaluation, and delivery of models into operational workflows-with a preference for candidates with experience applying natural language processing (NLP) and computer vision methods and tools.
Candidates should have a foundational understanding of machine learning methods and practical familiarity with common ML libraries and frameworks (e.g., PyTorch/torch, scikit-learn, SciPy), along with experience deploying and maintaining ML systems using modern engineering practices such as CI/CD, workflow orchestration, and monitoring. Successful applicants will also be comfortable collaborating on interdisciplinary teams and communicating complex technical work through technical deliverables and briefings for government stakeholders.
Successful candidates will contribute to a portfolio of government-sponsored projects addressing emerging challenges in areas such as decision support, information processing, human-machine teaming, and operational analytics, with particular emphasis on delivering ML capabilities that are reliable, testable, and maintainable. Work may include rapid prototyping as well as production-oriented engineering to transition research into usable tools, including interactive applications that enable end users to apply ML models in real-world contexts. Final appointment title and responsibilities will be based on qualifications and matched to programmatic needs.
Roles and Responsibilities
Roles and Responsibilities will vary by project and candidate expertise and may include:
Building end-to-end ML systems from technical problem formulation through training data selection/curation, modeling, evaluation, and delivery of ML models into usable tools and workflows, preferably with a focus on natural language programming and computer vision methods and tools
Applying core ML theory and methods in practice, including selecting appropriate approaches, implementing baselines, conducting error analysis, and iterating on model performance using common libraries and frameworks (e.g., PyTorch/torch, scikit-learn, SciPy)
Deploying and maintaining ML systems in development and operational environments, including git-based CI/CD, workflow orchestration, model packaging and Docker-based deployment, and monitoring for system health, data quality, and model performance over time
Developing interactive ML-enabled applications for end users, including front-end development using FastAPI + React (including Vite) and/or MERN/PERN stacks to deliver intuitive user experiences powered by ML models
Supporting proof-of-concept back-end development and requirements generation, including prototyping data stores and retrieval patterns and translating findings into clear requirements for a back-end engineering team (e.g., using Postgres (including pgvector), MongoDB, and/or ElasticSearch)
Collaborating with interdisciplinary teams including researchers, engineers, domain experts, and analysts to integrate ML capabilities into broader systems and mission workflows
Preparing technical deliverables and briefings for government stakeholders, translating complex technical work into clear, decision-relevant products (e.g., reports, slide briefings, memos, and research summaries)
Contributing to research proposals and technical work plans, including scoping technical approaches, estimating effort, identifying risks, and supporting sponsor engagement as needed
Must be able to obtain a U.S. security clearance. If selected, you must meet the requirements for access to classified information and will be subject to a government security clearance investigation that includes criminal and credit history checks, as well as verification of U.S. citizenship, birth, education, employment, and military history.
Final offer is contingent upon the candidate's ability to successfully obtain the necessary interim Secret security clearance, as determined by the U.S. Government, prior to commencing employment.
Qualifications
ARLIS is hiring at all levels in two complementary tracks: Research Specialist and Research Engineer.
Research Specialist Qualifications:
Entry Level:
Bachelor's degree in a relevant field such as Computer Science, Computer Engineering, Software Engineering, Data Science, or related discipline, plus relevant experience.
~2 years of demonstrated experience in organizing and managing projects through volunteer, extracurricular, or work activities
Demonstrated potential for excellence in the execution, administration, and/or management of research or academic programs
Ability to work as part of a multi-disciplinary opportunity team in a matrixed organization with a collaborative and team-centric culture
Strong oral and written communication skills
Excellent analytical and deep-dive skills
Mid-Level:
Master's degree in a relevant field such as Computer Science, Computer Engineering, Software Engineering, Data Science, or related discipline, plus relevant experience and 3+ years of experience in a technical role or project management position for defense or intelligence R&D programs with experience in technology assessment, systems design, system analysis, executing on multiple technical programs with scheduled deliverables, and communicating and interfacing with government customers; or Bachelor's Degree and 5+ years of relevant experience in a role of equivalent responsibility
Superior ability to deliver excellence in the execution, administration, and/or management of research or academic programs
Interact with U.S. government sponsors, customers, and stakeholders
Ability to work as part of a multi-disciplinary opportunity capture team in a matrixed organization with a collaborative and team-centric culture
Strong oral and written communication skills
Excellent analytical and deep-dive skills
Senior-Level:
Master's degree in a relevant field such as Computer Science, Computer Engineering, Software Engineering, Data Science, or related discipline, plus relevant experience and 7+ years of experience in a technical role or project management position for defense or intelligence R&D programs with experience in technology assessment, systems design, system analysis, executing on multiple technical programs with scheduled deliverables, and communicating and interfacing with government customers; or Bachelor's Degree and 10+ years of relevant experience in a role of equivalent responsibility
Superior ability to deliver excellence in the execution, administration, and/or management of research or academic programs
Knowledge of DoD appropriations and requirements processes
Lead engagements with U.S. government sponsors, customers, and stakeholders
Ability to work as part of a multi-disciplinary opportunity capture team in a matrixed organization with a collaborative and team-centric culture
Strong oral and written communication skills
Excellent analytical and deep-dive skills
Research Engineer Qualifications:
Assistant Research Engineer:
PhD plus 5 years of research experience in a relevant field such as Computer Science, Computer Engineering, Software Engineering, Data Science, or related discipline; including success leading research projects and a record of engineering achievement and show promise of continued productivity
Ability to:
Initiate new projects with long-term research goals, tackling more complex problems than an Assistant Research Engineer, leading work on multiple, concurrent projects, and managing cross-functional engineering teams
Serve as Principal Investigator or having primary responsibility for a significant part of a project
Interact with U.S. government sponsors, customers, and stakeholders
Expected to identify funding opportunities and serve as Principal Investigator on large proposals
Mentor junior staff and Professional Track Faculty Specialists and participating in their promotion sub-committees
Associate Research Engineer:
PhD plus 5 years of PhD-level research experience, including success capturing and leading large projects and a record of significant engineering achievement and show promise of continued productivity
Recognized as an authoritative subject matter expert and receive commensurate recognition
Ability to:
Initiate new projects with long-term research goals, tackling more complex problems than an Assistant Research Engineer, leading work on multiple, concurrent projects, and managing cross-functional engineering teams
Serve as Principal Investigator or having primary responsibility for a significant part of a project
Interact with U.S. government sponsors, customers, and stakeholders
Identify funding opportunities and serve as Principal Investigator on large proposals
Mentor junior staff and Professional Track Faculty Specialists and participating in their promotion sub-committees
Full Research Engineer:
Ph.D. with at least 10 years of PhD-level research experience, including success capturing and leading large projects and a record of significant engineering achievement and show promise of continued productivity
Established reputation for outstanding engineering practice, design, and development and viewed nationally as an authoritative subject matter expert
Proven Ability to:
Tackle problems of considerable scope and complexity with currently non-existent solutions requiring unconventional, novel approaches and sophisticated research techniques.
Pursue funding opportunities and serve as Principal Investigator or have primary responsibility for a significant part of a multi-investigator project
Lead the design and implementation of large projects with many components (subcontractors, teams, etc.).
Lead engagements with U.S. government sponsors, customers, and stakeholders
Build and execute new research programs
Hold leadership positions within ARLIS, on campus, or professional committees
Mentor junior staff and Professional Track Faculty Specialists and participating in their promotion sub-committees
Physical Demands:
Sedentary work performed in a normal office environment; exerts up to 10 pounds of force occasionally and/or negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Ability to attend meetings both on and off campus. Spending long hours in front of a computer screen.
Preferences:
Active TS/SCI
Licenses/ Certifications: N/AMinimum Qualifications

The appointee shall hold a Bachelor's degree in a relevant area and show potential for excellence in the administration and/or management of academic or research programs. Faculty Specialists are expected to engage in activities such as developing curriculum and/or innovative means for delivering curriculum, supervising the non-research activities of graduate or post-doctoral students, serving as grant writers or authors of other publications for an academic or research program, conducting specialized research duties or other such duties that would generate intellectual property to which the faculty member shall retain the rights. Appointments to this rank are typically one to three years and are renewable.

Additional Job Details

Required Application Materials: Cover Letter, Resume, List of References

Best Consideration Date: N/A

Posting Close Date: 11/30/26

Open Until Filled: Yes

DepartmentVPR-Applied Research Lab for Intelligence & SecurityWorker Sub-Type Faculty RegularSalary Range$49,072 - $252,288Background Checks

Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regardingdisclosablebackground checkinformation. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.

Employment Eligibility

The successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.

EEO Statement

The University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University's Equal Employment Opportunity Statement of Policy.

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