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Part Time Pytorch Jobs (NOW HIRING)

Reddit

Machine Learning Engineer

New York, NY · On-site

$223K - $260K/yr

Part-time telecommuting is an option. Hybrid work from Reddit offices in New York, NY. Minimum ... PyTorch); (7) Machine Learning deployment; (8) Model training pipeline (Kubeflow and Ray); (9) ...

TEGNA Inc.

Director, AI & Automation

New York, NY · On-site

$175K - $200K/yr

Proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn. * Expertise in cloud ... Our 401(k) program offers full, part-time and temporary employees the opportunity to contribute ...

Uottawa

APTPUO Winter 2027- MIA5100- (ONLINE)

Campus, IL · On-site

$239.47/hr

Professeur a temps-partiel regulier / Regular Part-Time Professor Date Posted (YYYY/MM/DD): 2026/06 ... such as Scikit-learn, PyTorch or TensorFlow, NLP frameworks, Transformer-based models, and ...

Ancestry

Machine Learning Engineer, Co-op

This is a part-time, work-study-based opportunity for active students in master's and PhD programs ... Proficient in Python and familiar with ML libraries such as TensorFlow, PyTorch or Scikit-learn.

Booz Allen Hamilton, Inc.

AI/ML Engineer, Senior

Dayton, OH · On-site

$99K - $225K/yr

... PyTorch, TensorFlow, or scikit-learn * Experience designing, configuring, or deploying software ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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Part Time Pytorch information

How do part-time PyTorch developers typically collaborate with full-time team members on machine learning projects?

Part-time PyTorch developers often work closely with full-time data scientists, machine learning engineers, and project managers through regular check-ins, code reviews, and collaborative platforms like GitHub or Slack. Clear communication and well-documented code are essential to ensure smooth handoffs and project continuity. It's common to be assigned specific modules or tasks, contributing to larger models, experiments, or data pipelines. Flexibility in scheduling and proactive updates help maintain alignment with the team's goals and deadlines.

What is the difference between Part Time Pytorch vs Part Time Machine Learning Engineer?

AspectPart Time PytorchPart Time Machine Learning Engineer
Required CredentialsKnowledge of Pytorch, basic programming skills, possibly some certifications in AI/MLSimilar; often requires experience with ML frameworks, programming, and relevant certifications
Work EnvironmentRemote or freelance projects, research labs, startupsRemote or onsite, startups, tech companies, research institutions
Industry UsageUsed mainly for deep learning model development and experimentationApplied in deploying ML models, data analysis, and AI product development

Part Time Pytorch roles focus on developing and experimenting with deep learning models using the Pytorch framework, often in research or freelance settings. Part Time Machine Learning Engineer positions involve broader responsibilities, including deploying ML solutions and working across various frameworks. Both roles require similar skills but differ in scope and application.

What are part-time PyTorch jobs?

Part-time PyTorch jobs are positions where employees work fewer hours than a standard full-time schedule and primarily use the PyTorch machine learning library. These jobs may involve developing, training, or deploying deep learning models for tasks such as computer vision, natural language processing, or data analysis. Part-time roles are ideal for students, freelancers, or professionals looking to gain experience with PyTorch while maintaining a flexible work schedule. Typical employers include tech companies, research labs, and startups working on AI projects.

What are the key skills and qualifications needed to thrive as a Part-Time PyTorch Developer, and why are they important?

To thrive as a Part-Time PyTorch Developer, you need strong programming skills in Python, a solid understanding of machine learning concepts, and hands-on experience with the PyTorch framework. Familiarity with related tools such as NumPy, pandas, Git, and cloud platforms is often required, along with relevant certifications in AI or machine learning being advantageous. Problem-solving abilities, effective communication, and time management are essential soft skills for success in a part-time, often remote, role. These skills ensure you can develop, debug, and deploy machine learning models efficiently while collaborating effectively with teams and managing flexible schedules.
What cities are hiring for Part Time Pytorch jobs? Cities with the most Part Time Pytorch job openings:
What are the most commonly searched types of Pytorch jobs? The most popular types of Pytorch jobs are:
Part Time Pytorch jobs near you
Adjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)

Adjunct Associate Faculty, Applied Generative AI (On-Campus, Fall '26)

Columbia University

New York, NY • On-site

$2.0K - $3.0K/wk

Part-time

Posted 29 days ago

Job description

Company Description
Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds to pursue greater human understanding, pioneering discoveries, and service to society.
The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.
Job Description
Seeking analytics professionals to serve as a part-time Associate for a graduate-level course on Applied Generative AI. An Associate is a faculty line junior to a Lecturer, that provides subject matter expertise and supports the instructional process for a course section. Serving as an Associate is an outstanding way to gain exposure to graduate-level teaching at Columbia University.
The Applied Generative AI course provides students with a comprehensive introduction to a branch of machine learning called generative modeling, focusing on the underlying concepts, theoretical techniques, and practical applications. Students will learn to use, fine-tune, and programmatically interface with high-level APIs and open-source foundational models, allowing them to leverage state-of-the-art tools in Generative AI. Additionally, the course delves into the theory and practice of low-level implementations, empowering students to train their own models on their own data and understand these models from first principles. The course covers various types of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and Transformers with their applications to text, image, audio, and video generation.
Responsibilities
  • Attend all class sessions, assist with instruction, lead breakout sessions, facilitate discussions.
  • Evaluate, grade student work and assessments as requested by the course Lecturer.
  • Monitor and address student concerns and inquiries.

Qualifications
Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting.
Requirements
  • Graduate degree in an area related to Machine Learning, Computer Science, Applied Mathematics, or related field.
  • 3+ years of related applied professional experience.

Preferred Skills & Experience
  • Programming experience in Python and experience with major deep learning frameworks such as PyTorch or TensorFlow.
  • Knowledge of deep learning architectures, such as CNNs, VAEs, GANs, and RNNs.
  • Experience with deploying code on cloud platforms such as AWS, GCP, or Azure.
  • Knowledge of Mathematics and Probability concepts used in machine learning, including
  • Optimization, Gradient Descent, Conditional Probability, Bayes Theorem, and Normal Distribution.

Additional Information
Salary range: $2,000 - $3,000 per semester long course
Please submit a resume inclusive of university teaching experience.
All your information will be kept confidential according to EEO guidelines.
Columbia University is an Equal Opportunity Employer / Disability / Veteran

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