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Scientific Machine Learning Jobs in Tennessee (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Chattanooga, TN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Memphis, TN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Inovalon

Senior Machine Learning Engineer

Nashville, TN · On-site

$118K - $156K/yr

... Science, Machine Learning, or equivalent practical experience preferred. Company : A technology company combining data analytics and targeted interventions to achieve meaningful impact across the ...

Inovalon

Senior Machine Learning Engineer

Nashville, TN · On-site

$118K - $156K/yr

... Science, Machine Learning, or equivalent practical experience preferred. Company : A technology company combining data analytics and targeted interventions to achieve meaningful impact across the ...

Varsity Tutors

Machine Learning Tutor

Knoxville, TN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Murfreesboro, TN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Kingsport, TN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Nashville, TN · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related field * 7+ years of professional experience, including significant hands-on machine learning development * Strong ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN

$100K - $138K/yr

Bachelor's degree in Computer Science, Engineering, Applied Mathematics, or a related field * 7+ years of professional experience, including significant hands-on machine learning development * Strong ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Tennessee

Scientific Machine Learning information

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What are popular job titles related to Scientific Machine Learning jobs in Tennessee? For Scientific Machine Learning jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Tennessee look for? The top searched job categories for Scientific Machine Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Scientific Machine Learning jobs? Cities in Tennessee with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Tennessee as of June 2026, with employment types broken down into 3% As Needed, 88% Full Time, 6% Part Time, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.
Nonproliferation Data Scientist

Nonproliferation Data Scientist

Oak Ridge National Laboratory

Oak Ridge, TN • On-site

Full-time

Posted 9 days ago

Oak Ridge National Laboratory rating

9.3

Company rating: 9.3 out of 10

Based on 15 frontline employees who took The Breakroom Quiz

3rd of 103 rated laboratories

Job description

Requisition Id 16639
Overview:
We are seeking a Nonproliferation Data Scientist to join the Data Science and Engineering for Nonproliferation Group in the National Security Sciences Directorate. In this role, you will develop and apply advanced data science, machine learning, and statistical approaches to challenging problems in nuclear nonproliferation and national security.
The successful candidate will work closely with multidisciplinary teams of data scientists, software engineers, physicists, and domain experts to develop innovative analytic capabilities that support nuclear material detection, characterization, safeguards, and nuclear fuel cycle analysis. This position provides the opportunity to conduct impactful research while contributing to the development of next-generation scientific software and data-driven methods for national security applications.
Major Duties and Responsibilities
  • Conduct research and development applying machine learning, statistical modeling, optimization, and data science methods to nuclear nonproliferation challenges.
  • Develop, evaluate, and apply data-driven algorithms, selecting appropriate analytical approaches based on problem characteristics, available data, and mission objectives.
  • Develop and maintain scientific software and analytic tools that enable advanced data analysis, modeling, and decision support.
  • Collaborate with multidisciplinary teams of domain scientists, software developers, and researchers to integrate advanced analytics into mission applications.
  • Design and execute computational studies to assess algorithm performance, quantify uncertainty, and generate actionable insights from complex datasets.
  • Communicate research findings through technical reports, publications, presentations, and interactions with sponsors and collaborators.
  • Contribute to proposal development, program growth activities, and new research initiatives.
  • Ensure all work is performed safely, securely, and in accordance with ORNL policies and procedures.

All team members deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. We foster a respectful, team-focused environment where all individuals can contribute and succeed.
Basic Qualifications
  • PhD in data science, computer science, statistics, mathematics, physics, engineering, or a related quantitative field; or an MS in one of these disciplines with a minimum of two years of relevant experience.
  • Demonstrated experience applying machine learning, statistical analysis, optimization, or related data science techniques to solve complex technical problems.
  • Experience developing software for scientific computing, data analysis, or machine learning applications.
  • Proficiency in Python and common scientific computing and machine learning libraries.
  • Strong written and verbal communication skills, including experience presenting technical results to scientific or technical audiences.

Preferred Qualifications
  • Experience with machine learning, artificial intelligence, statistical modeling, uncertainty quantification, optimization, or scientific machine learning methods.
  • Demonstrated ability to evaluate alternative analytical approaches and determine when different algorithms or modeling techniques are most appropriate for a given problem.
  • Experience with research software development practices, including version control, testing, reproducibility, and collaborative software engineering.
  • Experience with open-source scientific software projects.
  • Familiarity with high-performance computing, cloud computing, or large-scale data analytics environments.
  • Knowledge of nuclear nonproliferation, safeguards, nuclear fuel cycle analysis, remote sensing, or related national security mission areas.
  • Record of peer-reviewed publications, conference presentations, or other research accomplishments.
  • Experience working in multidisciplinary research environments involving both domain scientists and software developers.
  • Familiarity with modern AI/ML frameworks such as PyTorch, TensorFlow, JAX, or related tools.

Special Requirements:
  • This position requires the ability to obtain and maintain a Secret Compartmented Information (SCI) clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. In addition, due the SCI, you may also be subject to random polygraph testing.

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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