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Ml Inference Jobs in Powell, TN (NOW HIRING)

Ml Inference information

See Powell, TN salary details

$31.8K

$103.9K

$166.4K

How much do ml inference jobs pay per year?

As of Sep 3, 2026, the average yearly pay for ml inference in Powell, TN is $103,940.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,400.00 and $115,200.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What cities near Powell, TN are hiring for Ml Inference jobs?

Cities near Powell, TN with the most Ml Inference job openings:

Postdoctoral Research Associate - Scientific Validation of Quantum Simulations

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

$60 - $80/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago


Oak Ridge National Laboratory rating

8.8

Company rating: 8.8 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

15th of 121 rated laboratories


Job description

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Postdoctoral Research Associate - Scientific Validation of Quantum Simulations

We are seeking a Postdoctoral Research Associate to advance the scientific validation of quantum simulations for quantum materials. This work directly supports the five-year mission of the ORNL Quantum Science Center (QSC) to establish a quantum-accelerated computing ecosystem for scientific applications. The successful candidate will develop, test, and evaluate the scientific applications by comparing results from quantum simulations directly with experimental measurements and classical simulations of quantum materials. This work will include benchmarking simulations by using reliable classical reference calculations and extending toward more challenging regimes. As part of our team, you will work closely with ORNL staff and external collaborators in quantum computing, condensed-matter physics, neutron scattering, applied mathematics, and scientific computing.

This position resides within the Quantum Sensing and Computing Group in the Computational Sciences and Engineering Division (CSED), Computing and Computational Sciences Directorate (CCSD) at Oak Ridge National Laboratory (ORNL).

Major Duties/Responsibilities:
  • Lead the development, testing, and application of rigorous approaches for the evaluation and validation of quantum simulations of quantum materials, including realistic treatment of uncertatinty and systematic error across experimental, classical computing, and quantum computing workflows.
  • Extend the methodology to early fault-tolerant quantum simulations and, ultimately, to classically intractable regimes, establishing the rigorous evidence needed to support credible claims of quantum advantage.
  • Develop and apply physics-informed AI/ML and digital-twin capabilities to improve modeling, parameter inference, uncertainty assessment, and adaptive feedback between experiments, classical simulations, and quantum simulations.
  • Collaborate with ORNL staff scientists and external collaborators.
  • Write peer-reviewed scientific articles and present research findings at major scientific conferences.
  • Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service.
Basic Qualifications:
  • A Ph.D. degree in Physics, Applied Mathematics, Computer Science, Electrical Engineering, or a related discipline.
  • Familiarity with quantum computing and/or digital quantum simulation theory and practice.
  • Familiarity with quantum and classical programming languages and scientific computing.
Preferred Qualifications:

We welcome candidates with strengths in several of the following areas; no single candidate is expected to bring expertise in all of them:

  • Experience developing or implementing quantum algorithms for Hamiltonian simulation.
  • Background in quantum materials or quantum many-body physics, particularly quantum magnetism and strongly correlated systems, as well as classical methods such as exact diagonalization, tensor networks or DMRG, and quantum Monte Carlo.
  • Familiarity with inelastic neutron scattering, thermal transport, or related experimental probes, including the effects of instrumental resolution, data reduction, and observable reconstruction.
  • Experience with uncertainty quantification, covariance modeling, sensitivity and robustness analysis, Bayesian inference, inverse problems, parameter estimation, or model validation.
  • Experience or strong interest in scientific AI/ML, including surrogate or multi-fidelity modeling, digital twins, generative models, adaptive optimization, or autonomous experiment-simulation workflows.
  • Excellent written and oral communication skills.
  • Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory.
  • Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to ever changing needs.
Special Requirements:

Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree requirements before starting their appointment. The appointment length will be up to 24 months with the potential for extension. Initial appointments and extensions are subject to performance and availability of funding.

  • Letters of Recommendation: Please submit three letters of reference when applying to this position. You may upload these directly to your application or have them sent to
  • Security, Credentialing, and Eligibility Requirements: For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.
  • To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
  • For foreign national candidates:
  • If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
About ORNL:

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.


If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.


ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.

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