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Quantum Machine Learning Engineer Jobs in Oak Ridge, TN

Varsity Tutors

Data Science Tutor

Knoxville, TN · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

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Python Tutor

Knoxville, TN · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

FirstBank

Senior Automation Developer

Knoxville, TN · Remote

TN, KY, AL, GA, NC Summary: We're in search for a Senior Automation Developer that is ready to ... Knowledge of artificial intelligence and machine learning. * Understanding of workflow-based logic.

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Quantum Machine Learning Engineer information

See Oak Ridge, TN salary details

$30.1K

$123.1K

$185K

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

As of Sep 5, 2026, the average yearly pay for quantum machine learning engineer in Oak Ridge, TN is $123,109.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,000.00 and $148,200.00 per year, depending on experience, location, and employer.

What is a quantum machine learning engineer?

A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.

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

To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.

How do quantum machine learning engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, focusing on developing algorithms that leverage quantum hardware. The field is emerging with high growth potential, requiring skills in quantum algorithms, programming languages like Python, and understanding of both quantum mechanics and machine learning principles. As quantum technology advances, demand for specialists in this area is expected to increase, making it a promising career path for those with relevant expertise.

What job categories do people searching Quantum Machine Learning Engineer jobs in Oak Ridge, TN look for?

The top searched job categories for Quantum Machine Learning Engineer jobs in Oak Ridge, TN are:

What cities near Oak Ridge, TN are hiring for Quantum Machine Learning Engineer jobs?

Cities near Oak Ridge, TN with the most Quantum Machine Learning Engineer job openings:

Quantum Machine Learning Engineer jobs near you
Infographic showing various Quantum Machine Learning Engineer job openings in Oak Ridge, TN as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 27% Part Time, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $123,109 per year, or $59.2 per hour.

Post-Doctoral Research Associate: Department of Electrical Engineering and Computer Science - UTK

The University of Tennessee

Knoxville, TN • On-site

Full-time

Medical, Retirement, PTO

Re-posted 20 days ago

Job description


The research group of Dr. Suya in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville (UTK) is seeking a Postdoctoral Research Associate to contribute to externally funded research in trustworthy AI, adversarial machine learning, and the security of physical/cyber-physical AI systems. The position is for one year in the first instance, with the possibility of extension contingent on performance and funding. The successful candidate will lead and contribute to research projects at the intersection of trustworthy AI, security and privacy of cyber-physical and IoT systems, and physical-layer adversarial attacks against AI-enabled sensing and recognition systems. The position offers significant autonomy in shaping research directions, opportunities to co-author publications at top venues (CCS, NDSS, USENIX Security, IEEE S&P), mentor graduate/undergraduate students, and participate in proposal development for federal funding agencies (NSF, DARPA, ARO, DoE).
Responsibilities
  • Lead and participate in research projects in one or more of the following areas: trustworthy AI; security and privacy of cyber-physical and IoT systems; side-channel attacks and defenses on AI workloads; or physical-layer attacks against AI-enabled sensing and recognition.
  • Co-advise and mentor graduate and undergraduate student researchers on related projects.
  • Co-author publications at top venues (e.g., CCS, NDSS, USENIX Security, IEEE S&P).
  • Contribute to proposal development for federal funding agencies (e.g., NSF, DARPA, ARO, DoE).

Qualifications
Required Qualifications
  • Education: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field (completed by start date).
  • Experience: Demonstrated record of peer-reviewed publications in security, machine learning, or cyber-physical systems.
  • Knowledge, Skills, Abilities: Strong programming skills (Python and/or C/C++) and experience with ML frameworks (PyTorch or TensorFlow); excellent written and verbal communication skills in English.

Preferred Qualifications
  • Education: Ph.D. with a dissertation focus in security, machine learning, cyber-physical systems, or a closely related area.
  • Experience: First-author publications at top-tier security venues (e.g., CCS, NDSS, USENIX Security, IEEE S&P); experience mentoring graduate or undergraduate researchers; service to the research community (paper reviewing, workshop organization).
  • Knowledge, Skills, Abilities: Expertise in one or more of: adversarial ML, side/covert channels, sensor-driven attacks, IoT/CPS security; background spanning both systems-level (embedded systems, signal processing, wireless/communications) and AI/ML research is a plus.

Work Location
  • Location: Knoxville, Tennessee
  • Onsite

Compensation and Benefits
  • Anticipated hiring range: Competitive, commensurate with experience. UTK provides comprehensive benefits including health insurance, retirement contributions, and paid time off.
  • Find more information on UT Benefits here

Application Instructions
For full consideration, please submit an application with the noted below attachments:
  • Curriculum Vitae (with full publication list)
  • Cover letter describing research interests, relevant experience, and career goals
  • Research statement (1-2 pages) on past work and proposed directions

All related inquiries should be directed to Fnu Suya at fsuya@utk.edu.
About The Department
The University of Tennessee, Knoxville (UTK) is an R1 research university located in Knoxville, Tennessee, with strong collaborative ties to Oak Ridge National Laboratory (ORNL) - one of the largest U.S. Department of Energy national laboratories - offering unique opportunities for joint research in AI security, cyber-physical systems, and high-performance computing.
The Min H. Kao Department of Electrical Engineering and Computer Science houses internationally recognized faculty and research programs spanning AI/ML, security, embedded and cyber-physical systems, computer architecture, and data science. Knoxville offers a low cost of living and quick access to the Great Smoky Mountains and Oak Ridge National Laboratory.
About Us
The University of Tennessee, Knoxville, has shaped leaders, changemakers, and innovative thinkers since its founding in 1794. The university is home to more than 38,000 students and 10,000 statewide employees-the Volunteers-who uphold the university's tradition of lighting the way for others through leadership and service.
UT Knoxville offers over 900 programs of study across 14 degree-granting colleges and schools. As Tennessee's flagship land-grant university, its footprint spans the entire state. The university holds the highest Carnegie classification for research activity and has deep partnerships with industry leaders and the US Department of Energy's largest multidisciplinary laboratory, Oak Ridge National Laboratory.
The Knoxville campus serves and recruits for UT Knoxville, including the Institute of Agriculture and the Space Institute, as well as the UT Institute of Public Service.
UT Knoxville considers its employees its number one asset. With values that focus on work-life balance, compensation, and innovation leadership, all Vols are supported to advance professionally. Employees have access to career development and coaching, continued education, and an extensive list of development and training possibilities. The Volunteer employee experience implements structures and practices to attract and retain top-tier talent, fostering a strong staff community and supporting a culture of involvement and engagement for everyone.
The university holds a strong commitment to its land-grant mission of learning and engagement, with a tradition of service and leadership that carries that Volunteer spirit throughout the state and around the world. It has been ranked nationally as "Best Employer for New Graduates," "One of America's Best Large Employers," and "Best Workplace for Women," and has been designated as "Best Place for Working Parents" by Forbes Magazine.
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