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What is a Part Time Artificial Intelligence Machine Learning job?

A Part Time Artificial Intelligence (AI) Machine Learning (ML) job involves working fewer hours than a full-time position, typically focusing on tasks related to building, training, and evaluating AI and ML models. These roles may include data preprocessing, developing algorithms, testing models, or assisting with research and development. Part-time AI/ML positions are ideal for students, professionals seeking flexible work schedules, or those looking to gain experience in the field while balancing other commitments. Responsibilities and required skills can vary depending on the employer and the specific project needs.

What are some typical projects or tasks assigned to part-time Artificial Intelligence Machine Learning professionals?

Part-time Artificial Intelligence Machine Learning professionals are often tasked with supporting ongoing model development, data preprocessing, and conducting exploratory data analysis. They may assist in training and evaluating models, annotating datasets, and preparing technical documentation. Collaboration is common with full-time team members, including data scientists, engineers, and project managers, to ensure smooth integration and deployment of models. These roles can offer exposure to real-world AI challenges without the commitment of a full-time position.

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

To thrive as a Part Time Artificial Intelligence Machine Learning professional, you typically need a solid background in mathematics, statistics, programming (often Python), and a relevant degree or coursework in computer science or data science. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, experience with data analysis tools, and sometimes certifications like Google AI or AWS Machine Learning are highly valued. Critical thinking, problem-solving, and effective communication are essential soft skills for translating complex technical findings into actionable insights and collaborating with cross-functional teams. These skills and qualifications ensure the ability to develop robust AI solutions efficiently and contribute meaningfully to projects, even in a part-time capacity.
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Part Time Artificial Intelligence Machine Learning jobs near you
Part-Time Lecturer - Applied Machine Intelligence (Arlington)

Part-Time Lecturer - Applied Machine Intelligence (Arlington)

Northeastern University

Arlington, VA • On-site

Part-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago

Job description

About the Opportunity
The College of Professional Studies at Northeastern University invites applications for a non-tenure track part time faculty lecturer in Applied Machine Intelligence on the Arlington Campus.
The College of Professional Studiesis one of ten colleges of Northeastern University, a nationally ranked private research university. Founded in 1960, the College provides lifelong experiential learning that unleashes the capacities of aspiring individuals in all stages and walks of life. The College teaches undergraduate, graduate, and doctoral students on campus and online in more than 90 programs.
Northeastern University will not provide H-1B, TN, O-1, E-3, or any other type of employment visa sponsorship for the successful applicant to this position, now or in the future. Furthermore, the successful applicant must be able to maintain valid work authorization in the United States throughout the entire appointment without Northeastern University's sponsorship for a visa.
Responsibilities
Qualified candidates must be prepared to work with global student populations.
The Master of Professional Studies in Applied AI is looking for part-time faculty to teach courses across the program with special emphasis on applied artificial intelligence, machine learning, natural language processing, computer vision, and experiential learning addressing business and technical challenges in industry.
Instructional areas include, but are not limited to:
  • Core AI courses: Applied Artificial Intelligence, Applied Machine Learning, Applied Natural Language Processing, Applied Computer Vision
  • Specialized areas: Deep Learning, Generative AI, Prompt Engineering, Conversational AI and Chatbots, Reinforcement Learning
  • Applied domains: Machine Learning for Cybersecurity, AI for 3D Imaging, Recommender Systems, Quantum AI, Blockchain AI, AI for Autonomous Systems
  • Foundational courses (for Connect pathway students): Python programming, Mathematical Concepts, Research Methods and Scientific Writing

The Applied AI degree is a multi-disciplinary, experience-based program that prepares professionals from diverse backgrounds to harness the transformative potential of artificial intelligence. Through courses and projects that focus on applied machine learning, AI implementation, ethical AI practices, and real-world applications, students learn to create AI solutions across manufacturing, healthcare, finance, and other industries. The program emphasizes accessibility, offering pathways for both technical and non-technical professionals to transition into AI-focused roles.
Qualifications
Minimum qualifications:
  • Terminal degree (Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or an aligned discipline
  • Demonstrated professional experience implementing AI/ML solutions in industry settings
  • Proficiency in Python and modern AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, or similar)

Strongly preferred:
  • 5+ years of professional experience in AI/ML development, implementation, or strategy roles
  • Demonstration of teaching, coaching, and/or training experience with a history of successful teaching (online/on-ground) at the graduate level strongly preferred
  • Experience teaching adult learners or working professionals
  • Expertise in one or more specialized areas: natural language processing, computer vision, generative AI, deep learning, conversational AI, reinforcement learning, or AI applications in specific domains (cybersecurity, 3D imaging, autonomous systems)
  • Understanding of AI ethics, governance, and responsible AI practices
  • Ability to make complex AI concepts accessible to learners from diverse academic backgrounds

Application Materials
Applicants should submit materials including a cover letter and vitae.
Successful faculty at Northeastern will be dynamic and innovative scholars with a record of teaching excellence and a commitment to fostering belonging in the university community. Thus, strong candidates for this faculty position will have the expertise, knowledge, and skills to build their pedagogy, and curriculum in ways that reflect and enhance this commitment. Please indicate how your expertise, knowledge, and skills have prepared you to contribute to this work in your cover letter.
Please direct questions to John Wilder at j.wilder@northeastern.edu.
Applications will be reviewed until the position is filled.
Position Type
Academic
Additional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.
Pay Range:
The per credit rate is $1,569.00.

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