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Part Time Tensorflow Jobs (NOW HIRING)

$18 - $20/hr

AND POSITION REQUIREMENTS The College of IST is seeking applicants for part-time job a part-time, ... Strong programming skills in Python; experience with PyTorch, TensorFlow, or similar deep learning ...

Telework Type: Part-Time Telework * Work Location: Reston, VA * Salary Range: 123,400 - 178,500 ... TensorFlow, or Hugging Face). * Demonstrated experience in AI model validation, testing, and ...

Telework Type: Part-Time Telework * Work Location: Reston, VA * Salary Range: 123,400 - 178,500 ... TensorFlow, or Hugging Face). * Demonstrated experience in AI model validation, testing, and ...

$35.71/hr

Familiarity with AI/ML frameworks such as Python, scikit-learn, TensorFlow, or equivalent tools ... FLSA: Non-Exempt Time Type: Part time Pay Rate: Hourly Additional Information: As an EEO employer ...

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Part Time Tensorflow information

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$37.5K

$122.7K

$196.5K

How much do part time tensorflow jobs pay per year?

As of Sep 5, 2026, the average yearly pay for part time tensorflow in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a part time TensorFlow developer?

Part-time TensorFlow jobs are positions that involve working with the TensorFlow machine learning framework on a reduced or flexible schedule, rather than full-time hours. These roles may include tasks such as developing, training, and deploying machine learning models, often for specific projects or short-term needs. Part-time TensorFlow jobs are ideal for students, freelancers, or professionals seeking flexible work arrangements while applying their expertise in artificial intelligence and deep learning.

What are the key skills and qualifications needed to thrive as a part time TensorFlow developer?

To excel as a Part-Time TensorFlow Developer, you need a solid grounding in Python programming, mathematics, and machine learning principles, often demonstrated by a relevant degree or coursework. Familiarity with TensorFlow, Keras, and tools like Jupyter Notebook or Git is typically required, and certifications in TensorFlow or related AI technologies are advantageous. Strong problem-solving, time management, and clear communication skills help you deliver quality results efficiently, especially in a part-time capacity. These competencies ensure effective model development and deployment, as well as smooth collaboration on distributed or flexible teams.

What are some common challenges faced by part time TensorFlow developers, and how can they overcome them?

Part-time TensorFlow developers often face challenges such as staying up-to-date with rapid advancements in machine learning, managing time effectively to meet project deadlines, and integrating their work with full-time team members. To overcome these, it’s helpful to maintain clear communication with the team, prioritize continuous learning through online resources, and use collaborative tools like Git for version control. Additionally, participating in regular code reviews and team meetings ensures alignment and smooth integration of your contributions.

What jobs use TensorFlow?

Jobs that use TensorFlow include machine learning engineer, data scientist, AI researcher, and deep learning engineer. These roles involve developing and deploying neural network models, often requiring programming skills in Python and familiarity with TensorFlow frameworks. Such positions are common in tech companies, research institutions, and industries focused on artificial intelligence and data analysis.
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What cities are hiring for Part Time Tensorflow jobs?

Cities with the most Part Time Tensorflow job openings:

What are the most commonly searched types of Tensorflow jobs?

The most popular types of Tensorflow jobs are:

Infographic showing various Part Time Tensorflow job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Post-Doctoral Fellow in Acoustics AF7772

The OSU/A&M System

Stillwater, OK • On-site

$46K - $62K/yr

Full-time, Part-time

Posted 4 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.