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Artificial Intelligence Machine Learning Internship Jobs in California

Sr. Machine Learning Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

... Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field or equivalent work experience Preferred Qualifications Experience working on search ranking, relevance ...

Preferred Qualifications Experience working on search ranking, relevance, recommendation or information retrieval MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Information ...

Preferred Qualifications Experience working on search ranking, relevance, recommendation or information retrieval MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Information ...

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Artificial Intelligence Machine Learning Internship information

What are the key skills and qualifications needed to thrive as an Artificial Intelligence Machine Learning Intern, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Intern, you need foundational knowledge in computer science, statistics, and mathematics, often supported by coursework or a degree in a related field. Familiarity with programming languages like Python, machine learning libraries such as TensorFlow or PyTorch, and experience using data analysis tools are typically required. Strong problem-solving abilities, curiosity, and effective communication skills help interns excel in collaborative, fast-paced environments. These skills and qualities are essential to contribute meaningfully to projects, learn quickly, and adapt to evolving technological challenges.

What types of projects can an Artificial Intelligence Machine Learning intern expect to work on during their internship?

As an AI/ML intern, you can expect to work on a variety of projects such as data preprocessing, model development, and performance evaluation. Interns often assist in building and testing machine learning models, analyzing large datasets, and contributing to the improvement of existing algorithms. You may also collaborate closely with data scientists, engineers, and product teams to solve real-world problems and help integrate AI solutions into business processes. These experiences provide valuable exposure to both research and practical applications in the field.

What is the difference between Artificial Intelligence Machine Learning Internship vs Data Science Internship?

AspectArtificial Intelligence Machine Learning InternshipData Science Internship
Required CredentialsBasic programming, math, and AI/ML knowledgeStatistics, programming, and data analysis skills
Work EnvironmentTech companies, research labs, startupsBusiness, finance, healthcare, tech firms
Employer & Industry UsageAI/ML-focused roles in tech and researchData analysis and insights across industries
Search & Comparison IntentUnderstanding AI/ML internship roles and skillsExploring data science internship opportunities

Artificial Intelligence Machine Learning internships focus on developing AI and ML models, requiring programming and math skills. Data Science internships emphasize analyzing data to generate insights, often involving statistics and data visualization. While both roles involve data and programming, AI/ML internships are more specialized in building intelligent systems, whereas Data Science internships focus on interpreting data for decision-making.

What is an Artificial Intelligence Machine Learning Internship?

An Artificial Intelligence (AI) Machine Learning (ML) Internship is a temporary position designed for students or recent graduates to gain hands-on experience in AI and ML fields. Interns work on real-world projects involving data analysis, model development, and the application of machine learning algorithms under the guidance of experienced professionals. These internships help individuals develop practical skills, build a professional network, and improve their understanding of current technologies and tools used in AI and ML. Interns may also participate in research, code reviews, and present their findings. This experience is valuable for pursuing a career in data science, AI engineering, or related fields.
What are the most commonly searched types of Artificial Intelligence Machine Learning jobs in California? The most popular types of Artificial Intelligence Machine Learning jobs in California are:
What job categories do people searching Artificial Intelligence Machine Learning Internship jobs in California look for? The top searched job categories for Artificial Intelligence Machine Learning Internship jobs in California are:
What cities in California are hiring for Artificial Intelligence Machine Learning Internship jobs? Cities in California with the most Artificial Intelligence Machine Learning Internship job openings:
Infographic showing various Artificial Intelligence Machine Learning Internship job openings in California as of July 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution.

Hybrid Visiting of Artificial Intelligence

devry

San Jose, CA

Other

Posted 3 days ago


Job description

Opportunity:

DeVry University focuses on developing long-term relationships with superior instructors who have high professional standards, excellent communication skills, enthusiasm and a commitment to providing the finest practitioner-focused education. We are seeking primarily industry professionals to teach and share their knowledge and experience with undergraduate and graduate students in a variety of fields.

  • Courses meet once or twice a week for eight weeks.
  • Face-to-face interaction is blended with technology (such as online discussions and online assignments) for an enhanced learning environment.
  • Faculty are responsible for facilitating student learning by teaching courses and programs in accordance with DeVry University requirements.
  • Faculty develop course syllabi and lesson plans and apply teaching techniques to best achieve course and programmatic objectives.
  • All DeVry instructors will participate in a comprehensive faculty training program and ongoing faculty development activities to ensure the highest quality instruction. 
  • DeVry University does not guarantee any specific number of work hours or assignments, which may vary based on the University’s needs and discretion.
  • As you explore this opportunity, we invite you to view this brief video highlighting how our faculty engage in meaningful student support.

Responsibilities:

  • Develops and provides students with an approved DeVry University syllabus that follows a template established by the local campus, and which includes the terminal course objectives.
  • Organizes, prepares, and regularly revises and updates all course materials.
  • Uses appropriate technological options for online technologies and course-related software, including Websites, e-mail, and online discussions for preparing the course and making it accessible to students.
  • Models effective oral and written communications that engage the students, provide clarity, and improve student learning. 
  • Sets clear expectations for the course by publishing course terminal objectives, assignment/examinations dates, and weight the distribution of various evaluation categories.
  • Ensures that the content and level of material included on exams correspond to the course terminal objectives.
  • Demonstrates consistency and fairness in the preparation and grading of exams and provides timely feedback to students.
  • Embraces and integrates the responsible use of AI technologies in the classroom to enhance teaching and learning outcomes.
  • Demonstrates the ability to recognize, evaluate, and address appropriate and inappropriate student use of AI tools in academic work.
  • Completes other duties as assigned.

Qualifications:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

  • A doctorate in Artificial Intelligence, Computer Science, Data Science, Information Systems, or a closely related field is required, with at least 18 graduate credit hours in artificial intelligence, machine learning, data science, or a related computational discipline.
  • Applicants must upload unofficial graduate-level transcripts with their application.
  • Degrees must be awarded by an institution accredited by an agency recognized by the U.S. Department of Education or the Council for Higher Education Accreditation, or by an international institution determined to hold equivalent accreditation.
  • Three to five years of applied professional experience in artificial intelligence, machine learning, data science, intelligent systems, or related computational technologies.
  • Demonstrated experience with AI-enabled software development, which may include machine learning pipelines, generative AI tools, data modeling, or full-stack application development integrating AI services.
  • Industry-recognized certifications or professional credentials relevant to artificial intelligence, machine learning, data science, or software development.
  • Strong subject matter expertise in AI concepts and technologies, combined with effective communication skills and the ability to explain complex technical topics to diverse learners.
  • Knowledge of ethical, responsible, and secure AI practices, including awareness of data governance, bias mitigation, and responsible AI deployment.
  • Faculty must have a commitment to ongoing professional development in instructional technology, digital literacy, and responsible AI practices.
  • Additional requirements driven by state licensing, institutional policy, or accreditation standards may apply.

Preferred Qualifications:

  • Industry certifications in Python programming, artificial intelligence, machine learning, or data science (e.g., PCEP or equivalent).
  • AI practitioner or engineer certifications (e.g., CAIP, Oracle GenAI, or comparable industry-recognized credentials).
  • Experience with AI development frameworks and tools, such as machine learning libraries, model deployment platforms, or generative AI systems.
  • Experience applying DevSecOps practices in AI or data-driven environments, including model lifecycle management and secure AI deployment.
  • Experience with programmatic or regional accreditation processes, including outcomes assessment and curriculum alignment.
  • Active membership or engagement in professional technology or AI-related organizations, contributing to ongoing industry awareness and innovation.
  • Experience integrating AI-assisted learning tools, immersive technologies, or intelligent tutoring systems into post-secondary instruction.
  • Two to five years of teaching experience at the post-secondary level, preferably in artificial intelligence, data science, programming, or emerging technology disciplines.

Pay:

Visiting Professor pay is based on level, credit hours taught per 8-week session, and location. 

  • Pay in the states of AZ, CA, IN and PA is paid at an hourly rate of either $22.00/hour or $23.50/hour.Â