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Machine Learning Part Time Jobs in Oklahoma (NOW HIRING)

DISHWASHER (PART TIME)

Edmond, OK ยท On-site

$15.50/hr

Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ... Polishes silver using burnishing machine tumbler, chemical dip, buffing wheel and hand cloth ...

STEWARD (PART TIME)

Alva, OK ยท On-site

$12/hr

Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ... Operates large electric machines such as dishwashers, sanitizers, trash compactors, and glass ...

Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ... Operates large electric machines such as dishwashers, sanitizers, trash compactors, and glass ...

Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ... Polishes silver using burnishing machine tumbler, chemical dip, buffing wheel and hand cloth ...

Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ... Operates large electric machines such as dishwashers, sanitizers, trash compactors, and glass ...

Our careers are filled with purpose and encourage learning, growth, and meaningful impact. Apply ... Operates large electric machines such as dishwashers, sanitizers, trash compactors, and glass ...

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Showing results 1-20

Machine Learning Part Time information

See Oklahoma salary details

$23.5K

$39.3K

$81.3K

How much do machine learning part time jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning part time in Oklahoma is $39,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,000.00 and $42,500.00 per year, depending on experience, location, and employer.

What is a machine learning part time job?

A Machine Learning Part Time job is a role where individuals work on ML-related tasks with a flexible or reduced schedule. These roles can involve data preprocessing, model development, evaluation, or deployment, depending on the organization's needs. Part-time positions are often suitable for students, freelancers, or professionals looking to gain experience while managing other commitments. They may be remote or on-site and can vary in duration and workload.

What are the typical responsibilities and expectations for a part-time machine learning role?

In a part-time machine learning position, you are generally expected to assist with data preprocessing, model development, and analysis of project results under the guidance of a senior data scientist or engineer. Your tasks might include cleaning datasets, coding algorithms, running experiments, and preparing reports or presentations for team meetings. The work is often project-based and requires regular communication with team members to ensure alignment on objectives and deliverables. This structure allows you to gain hands-on experience with real-world datasets and industry tools while maintaining a flexible schedule, making it ideal for students or professionals transitioning into the field.

What are the key skills and qualifications needed to thrive in the machine learning part time position, and why are they important?

To thrive as a Machine Learning Part Time professional, you need a strong foundation in statistics, programming (often Python or R), and knowledge of core machine learning algorithms, typically demonstrated through a degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow, Scikit-learn, or PyTorch and experience with data preprocessing tools or cloud platforms are commonly expected, and certifications like TensorFlow Developer can be beneficial. Effective communication, time management, and the ability to work independently are key soft skills for success in this role. These competencies enable you to efficiently contribute to projects, solve complex problems, and collaborate remotely or in hybrid team environments.

What are the most commonly searched types of Machine Learning jobs in Oklahoma?

The most popular types of Machine Learning jobs in Oklahoma are:

What are popular job titles related to Machine Learning Part Time jobs in Oklahoma?

For Machine Learning Part Time jobs in Oklahoma, the most frequently searched job titles are:

What job categories do people searching Machine Learning Part Time jobs in Oklahoma look for?

The top searched job categories for Machine Learning Part Time jobs in Oklahoma are:

Infographic showing various Machine Learning Part Time job openings in Oklahoma as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $39,319 per year, or $18.9 per hour.

Post-Doctoral Fellow in Acoustics AF7772

Stillwater, OK โ€ข On-site

$46K - $62K/yr

Full-time, Part-time

Posted 8 days ago


Job description

Post-Doctoral Fellow - Acoustics

Position Summary:

The School of Mechanical and Aerospace Engineering at Oklahoma State University invites applications for a part-time Post-Doctoral Fellow position to join Prof. Yangfan Liu’s research group. The successful candidate will lead interdisciplinary research at the intersection of machine learning, physical and computational acoustics, vibration/noise control, and signal processing.

This is a postdoctoral appointment intended for candidates seeking to contribute and manage ongoing sponsored research projects and supervise students. Ideal candidates will have a strong cross-disciplinary background in acoustics, audio/speech or acoustic signal processing, computational acoustics, and modern machine learning. Key responsibilities include conducting independent research, developing AI-acoustics methodologies with strong practical and translational value, managing projects, contributing to proposals and sponsor reports, preparing high-quality peer-reviewed publications, and mentoring graduate and undergraduate students. The position offers opportunities to collaborate with academic researchers, industrial partners, and students across multiple disciplines.

Responsibilities and Duties

50% – Research

  • Develop machine learning, deep learning, and physics-aware models for acoustics, vibration, NVH, audio/speech, and signal-processing applications.
  • Build surrogate models, inverse-design frameworks, and data-driven optimization methods for acoustic materials, computational acoustics, compressor/vehicle-cabin acoustics, or related vibroacoustic systems.
  • Design and perform experiments to validate developed methodologies and build proof-of-concept demos.
  • Prepare peer-reviewed publications in leading journals and conferences in acoustics, signal processing, machine learning, mechanical engineering, and related fields.
  • Develop reproducible code, analysis pipelines, and technical documentation to support research dissemination and technology transfer.

20% – Research Management

  • Manage day-to-day project tasks to meet sponsor requirements, research milestones, and publication timelines.
  • Coordinate research activities among faculty, students, and external collaborators; organize technical meetings and track deliverables.
  • Provide technical leadership on model development, data analysis, simulation/measurement workflows, and manuscript preparation.

20% – Proposal Development & Professional Service

  • Contribute to research proposals for federal agencies, industry sponsors, and university-industry collaborative programs.
  • Assist with grant management, sponsor communications, technical reporting, and partnership development.
  • Represent the research group at conferences, workshops, sponsor meetings, and professional events.
  • Participate in peer review, professional societies, and academic service activities as appropriate.

10% – Student Mentoring

  • Mentor graduate and undergraduate students in machine learning, acoustics, signal processing, simulation, and data analysis.
  • Guide students in research planning, coding practices, experiment/simulation design, data interpretation, technical writing, and presentations.

Qualifications:

  • Ph.D. in Mechanical or Aerospace Engineering, Acoustics, Electrical and Computer Engineering, Computer Science, Applied Physics, or a closely related field.
  • Strong background in acoustics, vibration/NVH, audio/speech processing, acoustic signal processing, computational acoustics, or related areas.
  • Demonstrated expertise in machine learning or AI methods, such as deep learning, physics-informed or physics-aware learning, surrogate modeling, inverse design, generative models, optimization, or uncertainty-aware modeling.
  • Strong record of scholarly research, including first-author or major-contribution publications in high-quality peer-reviewed journals and conferences.
  • Experience with numerical simulation, experimental/measurement data, acoustic materials/structures, vehicle-cabin acoustics, HAV equipment noise, aerodynamic noise, or speech/audio systems is preferred.
  • Proficiency in research programming and data analysis, preferably using Python and ML frameworks such as PyTorch or TensorFlow; experience with MATLAB, COMSOL, FEM/CFD/acoustic tools, or signal-processing toolchains is a plus.
  • Demonstrated ability to communicate complex technical concepts clearly in reports, manuscripts, presentations, and interdisciplinary team settings.
  • Experience mentoring students, coordinating research tasks, leading collaborative projects, or managing team deliverables is strongly preferred.

SALARY AND BENEFITS:

Salary will be commensurate with education, experience, qualifications, appointment percentage, and contingent on available funding. Benefits, if applicable, will follow Oklahoma State University policies for part-time postdoctoral appointments. Applicants should refer to Oklahoma State University Human Resources for current benefits information.

SPECIAL INSTRUCTIONS TO APPLICANTS:

The process of reviewing applications will begin soon and will continue until a successful candidate is selected.

Interested and qualified candidates should submit a single PDF file including:

  • a cover letter addressing research interests, relevant experience, and skills that fulfill the requirements;
  • a Curriculum Vitae;
  • up to three representative publications.

Questions about the position should be directed to Prof. Yangfan Liu at yangfan.liu@okstate.edu.