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Generative Ai Part Time Jobs in Illinois (NOW HIRING)

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Generative Ai Part Time information

What is a generative AI part time?

A Generative AI Part Time job involves working with artificial intelligence models that are designed to create new content, such as text, images, or music, based on training data. These roles can include tasks such as developing, fine-tuning, or evaluating generative AI models, as well as integrating them into applications. Part-time positions offer flexibility in work hours and are suitable for students, freelancers, or professionals seeking additional experience in AI. Common responsibilities may include data preparation, model testing, and collaborating with other team members on AI-driven projects.

What are the key skills and qualifications needed to thrive as a generative AI part time, and why are they important?

To thrive as a Generative AI Specialist (Part-Time), you typically need a background in computer science, machine learning, and experience with AI model development. Proficiency with tools like Python, TensorFlow, PyTorch, and familiarity with generative models such as GANs or LLMs, as well as relevant certifications, are highly valuable. Strong analytical thinking, creativity, and collaboration skills help individuals adapt to evolving project needs and work effectively with stakeholders. These capabilities are crucial for driving innovative AI solutions and ensuring project success within limited working hours.

What is the difference between Generative Ai Part Time vs Data Scientist Part Time?

AspectGenerative Ai Part TimeData Scientist Part Time
Required CredentialsRelevant AI/ML certifications, programming skillsStatistics, data analysis, programming certifications
Work EnvironmentTech companies, startups, freelance projectsResearch labs, tech firms, consulting
Employer & Industry UsageAI development, content creation, automationData analysis, predictive modeling, business insights

Generative Ai Part Time roles focus on creating AI models that generate content, requiring skills in AI/ML and programming. Data Scientist Part Time roles involve analyzing data to extract insights, often requiring similar technical credentials. While both roles operate in tech environments, Generative Ai positions emphasize AI model development, whereas Data Scientist roles focus on data analysis and interpretation.

Can you get a job with generative AI?

A job involving generative AI typically requires skills in machine learning, deep learning, and programming languages like Python. Roles may include AI researcher, data scientist, or AI engineer, often requiring experience with tools such as TensorFlow or PyTorch. Entry-level positions are available for those with relevant education or certifications in AI and related fields.

What are the most commonly searched types of Generative Ai jobs in Illinois?

The most popular types of Generative Ai jobs in Illinois are:

What are popular job titles related to Generative Ai Part Time jobs in Illinois?

For Generative Ai Part Time jobs in Illinois, the most frequently searched job titles are:

What cities in Illinois are hiring for Generative Ai Part Time jobs?

Cities in Illinois with the most Generative Ai Part Time job openings:

Infographic showing various Generative Ai Part Time job openings in Illinois as of August 2026, with employment types broken down into 100% Part Time. Highlights an 80% In-person, and 20% Remote job distribution.

APTPUO Fall 2026- MIA5150-REPOST (ONLINE) Topic (Generative AI and (LLMs)

Uottawa

Campus, IL โ€ข On-site

$239.47/hr

Part-time

PTO

Re-posted 27 days ago


Job description

Posting Reason:

New Position

Location:

Main Campus

Academic Period:

2026 Fall Semester

Faculty:

Faculte de genie / Faculty of Engineering

Academic Unit:

Ecole de conception et d'innovation pedagogique en genie \\ School of Engineering Design and Teaching Innovation

Course Title:

Generative AI and Large Language Models

Course Code:

MIA5150

Section:

B

Course Description:

Foundations and practices of Generative AI and Large Language Models (LLMs), covering the full lifecycle from model development to deployment. Explore generative model families, including Transformers, autoregressive models, diffusion models, GANs, and VAEs, and their multimodal applications across text, image, audio, and video. Modern techniques such as fine-tuning, parameter-efficient training, in-context learning, contrastive learning, retrieval-augmented generation (RAG), and multi-agent systems for enabling complex reasoning, coordination, and autonomous task execution are discussed. Key practices in prompt engineering, inference optimization, safety and alignment, and responsible AI deployment. Practical applications across diverse domains.
Prerequisite: MIA5100, MIA5126 or equivalent.

Posting limited to:

Professeur a temps-partiel regulier / Regular Part-Time Professor

Date Posted (YYYY/MM/DD):

2026/05/26

Applications must be received BEFORE (YYYY/MM/DD):

2026/08/23

Expected Enrolment:

30

Approval date:

2026/07/22

Number of credits:

3

Work Hours:

39

Hourly Rate:

Enseignement / Teaching: $239.47 (2024-2025)

The academic year starts on September 1 and ends on August 31.

These rates do not included vacation pay nor statutory pay.

These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.

Course type:

B

Posting type:

Regulier / Regular

Language of instruction:

Anglais | English

Competence in second language:

Active

Course Schedule:

Mardi | Tuesday 19:00-22:00 - -

Requirements:

  • Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Software Engineering, DTI, Engineering, or a closely related field.
  • Demonstrated expertise in Generative AI and Large Language Models (LLMs), including areas such as Transformers, diffusion models, GANs, VAEs, retrieval-augmented generation (RAG), prompt engineering, fine-tuning, and multimodal AI systems.
  • Experience developing or applying modern AI/ML workflows using industry-standard tools and frameworks such as Python, PyTorch, TensorFlow, Hugging Face Transformers, LangChain, vector databases, and cloud-based AI platforms.
  • Knowledge of AI deployment practices, including inference optimization, parameter-efficient training, model evaluation, safety, alignment, responsible AI, and scalable deployment architectures.
  • Knowledge of emerging agentic AI systems and multi-agent orchestration frameworks for autonomous reasoning, planning, and task execution.
  • Teaching experience at the graduate/undergraduate level in Artificial Intelligence, Machine Learning, Data Science, or related disciplines
  • Demonstrated ability to translate complex AI concepts into applied, industry-relevant learning experiences through lectures, labs, projects, and case studies.
  • Relevant industry experience in AI/ML development, applied Generative AI, MLOps, or AI product development is considered an asset.

Additional Information and/or Comments:

The course is online

An acceptable level of education and/or experience could be viewed as being equivalent to the educational required and/or demonstrated experience. If you are invited to continue the selection process, please notify us of any adaptive measures you might require. Information you send us will be handled respectfully and in complete confidence. Employees are required under provincial law to successfully complete all mandatory legislated training. The list of training may be modified by provincial law.

The hiring process will be governed by the current APTPUO collective agreements; you can click here for the main unit, here for the OLBI unit, or here for the Toronto/Windsor unit to find out more.

The University of Ottawa embraces diversity and inclusion in the workplace. We are passionate about our people and committed to employment equity. We foster a culture of respect, teamwork and inclusion, where collaboration, innovation, and creativity fuel our quest for research and teaching excellence. While all qualified persons are invited to apply, we welcome applications from qualified Indigenous persons, racialized persons, persons with disabilities, women and LGBTQIA2S+ persons. The University is committed to creating and maintaining an accessible, barrier-free work environment. The University is also committed to working with applicants with disabilities requesting accommodation during the recruitment, assessment and selection processes. Applicants with disabilities may contact vra.affairesprofessorales@uottawa.ca to communicate the accommodation need. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Prior to May 1, 2022, the University required all students, faculty, staff, and visitors (including contractors) to be fully vaccinated against Covid-19 as defined in Policy 129 - Covid-19 Vaccination. This policy was suspended effective May 1, 2022 but may be reinstated at any point in the future depending on public health guidelines and the recommendations of experts.