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Quantum Machine Learning Jobs in Chicago, IL (NOW HIRING)

Varsity Tutors

Linear Algebra Tutor

Naperville, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

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Linear Algebra Tutor

Buffalo Grove, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

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Linear Algebra Tutor

Chicago, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

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Linear Algebra Tutor

Des Plaines, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

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Linear Algebra Tutor

Highland Park, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Varsity Tutors

Linear Algebra Tutor

Schaumburg, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Varsity Tutors

Linear Algebra Tutor

Wheaton, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Varsity Tutors

Linear Algebra Tutor

Skokie, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Varsity Tutors

Linear Algebra Tutor

Oak Lawn, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Varsity Tutors

Linear Algebra Tutor

Evanston, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

Varsity Tutors

Linear Algebra Tutor

Lake Forest, IL · Remote

$18 - $40/hr

Emphasizes geometric interpretation of transformations and connects linear algebra to computer graphics, machine learning, and quantum mechanics applications. * Curriculum Awareness & Adaptive ...

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Showing results 21-40

All JobsQuantum Machine Learning JobsQuantum Machine Learning Jobs in Chicago, IL

Quantum Machine Learning information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

How much do quantum machine learning jobs pay per year?

As of Sep 4, 2026, the average yearly pay for quantum machine learning in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

What is a quantum machine learning?

A Quantum Machine Learning (QML) job involves applying principles of quantum computing to machine learning tasks. Professionals in this field develop algorithms that leverage quantum systems to improve computational efficiency and solve complex problems faster than classical methods. Responsibilities often include researching quantum algorithms, implementing quantum circuits, and working with tools like Qiskit or TensorFlow Quantum. These roles are typically found in research labs, tech companies, and startups exploring the intersection of AI and quantum technology. Strong backgrounds in quantum mechanics, linear algebra, and computer science are essential.

What does a quantum machine learning professional do?

Quantum Machine Learning professionals often work on exploratory projects at the intersection of quantum computing and artificial intelligence, such as developing new algorithms that leverage quantum hardware for faster data processing or optimizing classical ML models using quantum techniques. Daily tasks may include designing experiments, simulating quantum systems, analyzing results, and collaborating with physicists and software engineers. The work can range from foundational research to applied development, depending on the organization's focus. These roles frequently involve teamwork and staying updated on emerging academic and industry advances to ensure innovative problem-solving approaches.

What are the key skills and qualifications needed to thrive in quantum machine learning?

To thrive in Quantum Machine Learning, you need a solid background in quantum physics, machine learning, linear algebra, and programming—often supported by a graduate degree in a related field. Familiarity with quantum computing frameworks such as Qiskit or Cirq, and experience with conventional ML libraries like TensorFlow or PyTorch are typically expected. Strong problem-solving abilities, effective communication, and a collaborative mindset help professionals stand out. Mastery of these skills and qualities is essential for tackling complex interdisciplinary challenges and driving innovation in this rapidly evolving field.

Is quantum machine learning a good career?

Quantum machine learning is an emerging field combining quantum computing and machine learning, with growing research and industry interest. Careers in this area typically require strong backgrounds in quantum physics, computer science, and programming skills, often involving specialized tools like quantum algorithms and hardware. As the field develops, demand for experts is expected to increase, making it a promising career path for those with relevant expertise.

What are popular job titles related to Quantum Machine Learning jobs in Chicago, IL?

For Quantum Machine Learning jobs in Chicago, IL, the most frequently searched job titles are:

What job categories do people searching Quantum Machine Learning jobs in Chicago, IL look for?

The top searched job categories for Quantum Machine Learning jobs in Chicago, IL are:

Quantum Machine Learning jobs near you
Infographic showing various Quantum Machine Learning job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $43,867 per year, or $21.1 per hour.

Assistant Scientist - AI for Autonomous Synthesis and Multimodal Characterization

Argonne National Laboratory

Lemont, IL • On-site

Full-time

Re-posted 26 days ago

Job description

The Center for Nanoscale Materials (CNM) and the Advanced Photon Source (APS) at Argonne National Laboratory invite applications for a joint Assistant Scientist position focused on developing and applying artificial intelligence (AI) and machine learning (ML) methods for the autonomous, self-driving synthesis of nanoscale and quantum materials.
This is an exciting opportunity to help shape a new generation of closed-loop, AI-enabled experimental workflows that tightly integrate synthesis within situ and operando x-ray, electron, and optical characterization. The successful candidate will help bridge CNM's world-class capabilities in nanofabrication and chemical synthesis with APS's leading synchrotron measurement tools, enabling adaptive and autonomous exploration of complex materials design spaces.
In this role, you will lead a research program centered on AI-driven autonomous synthesis, including:
  • Active learning and Bayesian optimization over synthesis parameters such as precursors, temperature, sequences, and pressure
  • Generative and inverse-design models for materials discovery
  • Closed-loop feedback frameworks that use in situ/operando scattering, spectroscopy, and imaging to guide synthesis in real time
  • AI-enabled analysis of high-throughput, multimodal experimental data with uncertainty quantification
  • Integration of edge computing, high-performance computing (HPC), and scientific data infrastructure to support scalable, user-facing autonomous workflows across CNM synthesis platforms and APS beamlines

This position is a joint appointment between the Theory and Modeling Group at CNM and the Computational Science and AI Group (CAI) at APS. The successful candidate will have access to Argonne's exceptional ecosystem of facilities and expertise, including the upgraded APS, CNM's advanced synthesis and characterization capabilities, and leadership-class computing resources at the Argonne Leadership Computing Facility.
Key Responsibilities
  • Lead and develop a research program in AI-enabled autonomous materials synthesis
  • Design and implement closed-loop experimental workflows that integrate synthesis, characterization, and decision-making
  • Develop and apply AI/ML methods for active learning, optimization, inverse design, and experiment planning
  • Build analysis tools for multimodal, high-throughput experimental data, including real-time or near-real-time processing
  • Collaborate closely with scientists across materials synthesis, characterization, beamline science, theory, and computing
  • Contribute to the development of scalable computational and data workflows spanning edge, beamline, and HPC environments
  • Publish in peer-reviewed journals, present at scientific meetings, and help shape future directions in autonomous materials research

Position Requirements
  • Ph.D. in physical chemistry, inorganic chemistry, computational materials science, chemical engineering, or a related field, along with 3-6 years of postdoctoral research experience
  • A strong understanding of nanomaterials synthesis and/or in situ/operando x-ray characterization (including scattering, spectroscopy, or imaging), with demonstrated experience connecting the two
  • Proven experience developing and applying AI/ML methods to autonomous experimentation, closed-loop optimization, active learning, or inverse design
  • A strong publication record demonstrating innovation in AI/ML for materials synthesis, synchrotron experiments, or a closely related area
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
  • Experience with optimization and active-learning libraries such as BoTorch, GPyTorch, or scikit-learn
  • Strong programming skills, especially in Python, including integration with experimental control systems or lab-automation frameworks
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork

Preferred Qualifications
  • Experimental control and orchestration frameworks such as ROS, Bluesky, or EPICS
  • Laboratory automation and robotic synthesis platforms
  • Generative models, reinforcement learning, or agentic AI approaches for materials discovery and experiment planning
  • Multimodal data fusion and real-time data reduction for synchrotron or nanoscale experiments
  • High-performance computing (HPC), edge-to-HPC workflows, and scientific data infrastructure
  • Digital twins, physics-informed machine learning, or simulation-augmented experiment design
  • Excellent written and verbal communication skills, with the ability to work effectively in a highly collaborative, multidisciplinary environment

Application Materials
Please upload the following as part of your application:
  • Curriculum Vitae (CV)
  • Cover Letter

RD2: Bachelors and 5+ years of experience, Masters and 3+ years, or PhD and 0+ years, or equivalent
Job Family
Research Development (RD)
Job Profile
Materials/Ceramics/Metallurgical 2
Worker Type
Regular
Time Type
Full time
The expected hiring range for this position is $94,486.00 - $147,398.94.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
Click here to view Argonne employee benefits!
As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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