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Quantum Machine Learning Engineer Jobs in Oak Ridge, TN

Sedgwick

Principal Data Scientist

Knoxville, TN · On-site

Deep expertise in machine learning algorithms, statistical modeling techniques, and predictive analytics methodologies. * Strong programming skills in Python, R, or similar analytical languages.

DataAnnotation

SDLC Engineer - AI Trainer

Knoxville, TN · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

CGI Inc.

AI/ML Engineer

Knoxville, TN · On-site

AI/ML Engineer Category: Software Development/ Engineering Main location: United States, Tennessee ... Machine Learning * Python (Anaconda) AI/ML * Retrieval-Augmented Gen.(RAG) What you can expect from ...

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All JobsQuantum Machine Learning Engineer JobsQuantum Machine Learning Engineer Jobs in Oak Ridge, TN

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 Jul 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 the salary of quantum machine learning engineer?

The salary of a quantum machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in quantum algorithms and programming languages like Python or Qiskit may offer higher compensation. Many positions also include benefits such as research opportunities and access to advanced quantum computing tools.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum hardware. The field is emerging, with high demand for specialized skills in quantum algorithms, programming languages like Qiskit, and understanding of both quantum physics and data science. Careers in this area can be rewarding but often require advanced education and continuous learning due to rapid technological advancements.

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.

Will MLE be replaced by AI?

Quantum Machine Learning Engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum systems. While AI continues to advance, quantum computing is expected to complement classical machine learning rather than replace it entirely, and MLE roles will evolve to incorporate new quantum techniques and tools. Continuous learning in both quantum algorithms and machine learning is essential for professionals in this field.

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.

What are the key skills and qualifications needed to thrive as a Quantum Machine Learning Engineer, and why are they important?

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.
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
AI/ML for Power System Analysis, Power Flow, and State Estimation Fall Student Engineer

AI/ML for Power System Analysis, Power Flow, and State Estimation Fall Student Engineer

Electric Power Research Institute, Inc.

Knoxville, TN • On-site

$31 - $36/hr

Full-time

Medical, Retirement, PTO

Posted 18 days ago

Job description

Job Title:
AI/ML for Power System Analysis, Power Flow, and State Estimation Fall Student Engineer
Location:
Knoxville, TN
Job Summary and Description:
This is an internship position for a student to support R&D projects related to AI-driven power system modeling, including power flow, state estimation, and large-scale grid analytics under high renewable penetration. Looking for students who can work at minimum in the 2026 Fall semester (August-December).
Duties & Responsibilities:
The student must be familiar with the following:
  • Basic familiarity with integrating physical constraints (power flow equations, network limits) into data-driven models (physics-informed ML concepts)
  • Understanding of representing power systems as graphs and applying graph-based learning methods (e.g., graph neural networks)
  • Exposure to developing machine learning models (preferably deep learning) for power system applications
  • Working knowledge of AC/DC power flow, state estimation, and grid modeling fundamentals
  • Procedure of running power flow simulations using tools such as PSS®E, PSLF, Pandapower, or MATPOWER, and understanding system modeling workflows
  • Procedure of generating datasets using simulation tools for varying load, generation, and contingency conditions (N-1, N-k)

Qualifications:
  • Minimum 1 year of Master's or PhD (in Electrical Engineering focusing on Power systems)

Ideal Candidate:
  • Electrical engineering PhD student with emphasis on AI for power systems
  • Strong understanding of power flow and/or state estimation methods
  • Familiarity with power system simulation tools (preferably PSS®E, PSLF, Pandapower, or MATPOWER)
  • Strong programming skills (preferably in Python, MATLAB is a plus)
  • Experience with machine learning or deep learning frameworks (e.g., PyTorch or TensorFlow)
  • Exposure to graph neural networks will be considered a plus
  • Experience with data processing, numerical computing, and model development
  • Strong technical writing and presentation skills

The hourly rate range for Student positions are:
  • Undergraduate: $16-29 per hour
  • Masters: $27-33 per hour
  • Ph.D: $31-36 per hour

These ranges are an estimate, and the actual hourly rate may vary based on various factors, including without limitation applicant's education, experience, skills, and abilities, as well as internal equity and alignment with market data. The hourly rate may also be adjusted based on applicant's geographic location.
As an EPRI Student, you will not participate in EPRI's Benefit Programs which includes health insurance, retirement benefits, vacation, sick leave (except as set required by law) and holiday pay. However, as a Student employee you are eligible for the benefits of Social Security, State Disability Insurance, and Workers' Compensation Insurance.
For Student positions which require one to relocate to an EPRI office. Relocation assistance is not provided and the student will be responsible for covering all relocation costs/expenses.
EPRI participates in E-Verify, an online system operated jointly by the Department of Homeland Security and the Social Security Administration (SSA). EPRI uses the system to check the work status of new hires by comparing information from the employee's I-9 form against SSA and Department of Homeland Security databases.
EPRI is an equal opportunity employer. EEO/AA/M/F/VETS/Disabled
Together . . . Shaping the Future of Energy.
www.epri.com

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