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Machine Learning Quantum Computing Jobs in Maryland

IonQ

Senior Systems and Network Engineer

College Park, MD · On-site

$102K - $140K/yr

Our quantum computing services are available through all major cloud providers, while we also meet ... machines * Experience with Kubernetes or container orchestration in a bare-metal or hybrid ...

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Machine Learning Quantum Computing information

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.

What are the key skills and qualifications needed to thrive as a machine learning quantum computing specialist?

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 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 popular job titles related to Machine Learning Quantum Computing jobs in Maryland?

For Machine Learning Quantum Computing jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Machine Learning Quantum Computing jobs in Maryland look for?

The top searched job categories for Machine Learning Quantum Computing jobs in Maryland are:

What cities in Maryland are hiring for Machine Learning Quantum Computing jobs?

Cities in Maryland with the most Machine Learning Quantum Computing job openings:

Machine Learning Quantum Computing jobs near you
Infographic showing various Machine Learning Quantum Computing job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Engineer

Johns Hopkins University AppliedPhysicsLaboratory

Laurel, MD • On-site

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New

Job description

Description
Do you have demonstrated machine learning experience and want to apply that experience to solving a wide variety of complex problems in this rapidly evolving field?
Do you thrive in a collaborative research environment, working alongside an energetic, multidisciplinary team of scientists and engineers?
Are you ready to help the US secure and maintain leadership in the development and deployment of AI/ML algorithms for non-kinetic defense systems?
If so, we're looking for someone like you to join our team at APL!
We are seeking an experienced Machine Learning Engineer who will contribute to all phases of the machine learning algorithm development and implementation. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges.
As a Machine Learning Engineer, you will...
  • Design, implement, and evaluate advanced machine learning algorithms to solve challenging real-world planning, perception, coordination, and control problems in support of national defense.
  • Develop software pipelines to integrate data streams, simulation environments, and intelligent decision-making algorithms.
  • Work with technologies and concepts at the cutting edge of AI, including but not limited to: deep reinforcement learning, foundation models, large language models, convolutional/recurrent/graph neural networks, computer vision, and physics-based modeling and simulation tools.
  • Collaborate closely with the talented team of scientists and engineers in our group and with others across APL.
  • Engage directly with sponsors to communicate proposed concepts, solutions, and analysis.

Qualifications
You meet the minimum requirements for the job if you...
  • Have a Bachelor's degree in Mathematics, Physics, Engineering, Computer Science, or a related field.
  • Have at least 2+ years of experience in machine learning and data science fields.
  • Have at least one year of hands-on experience applying/developing machine learning algorithms using common libraries such as PyTorch or TensorFlow.
  • Have strong foundational knowledge in at least two of the following: classification, clustering, deep learning, reinforcement learning, computer vision (object detection and visual tracking), multi-agent systems, or optimization/control theory.
  • Have demonstrated experience in working with version control software like Git.
  • Have strong, effective communication skills both verbal and written.
  • Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You 'll go above and beyond our minimum requirements if you...
  • Have an MS in Mathematics, Physics, Engineering, Computer Science, or a related field.
  • Have 5+ years of experience in designing and implementing AI/ML algorithms for a variety of datasets.
  • Have proven experience applying state-of-the-art deep learning techniques to solve distributed resource allocation problems.
  • Have hands-on experience building computer vision pipelines for detection, tracking, segmentation, or multi-modal sensor fusion.
  • Have experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.
  • Are comfortable working in high performance computing environments (GPU/CPU clusters).
  • Have proficiency in one or more of the following technology areas: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI.
  • Have a track record of writing deployable, production-level code (Python, C/C++) for real-world applications.

#LI-KW1
About Us
Why Work at APL?
The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.
At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at ;br>
All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact
The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.
Minimum Rate
$100,000 Annually
Maximum Rate
$245,000 Annually

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