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Summer Artificial Intelligence Machine Learning 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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Summer Artificial Intelligence Machine Learning information

What types of projects can I expect to work on during a Summer Artificial Intelligence Machine Learning internship?

As a Summer Artificial Intelligence Machine Learning intern, you can expect to contribute to projects involving data preprocessing, model training, and evaluation under the guidance of experienced mentors. Typical tasks may include developing and testing new algorithms, analyzing large datasets, and supporting the deployment of machine learning models. You'll often collaborate closely with data scientists, software engineers, and other interns, gaining exposure to real-world AI challenges and industry-standard tools. This hands-on experience not only builds technical skills but also improves teamwork and communication abilities, laying a strong foundation for a future career in AI and ML.

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

To thrive as a Summer Artificial Intelligence Machine Learning intern, you need a solid background in mathematics, statistics, and programming (often Python), typically supported by coursework or projects in machine learning or data science. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is commonly expected. Strong problem-solving skills, curiosity, and the ability to collaborate effectively within diverse teams are valuable soft skills for this role. These competencies are crucial for successfully developing, implementing, and refining AI models in a fast-paced, innovation-driven environment.

What is a Summer Artificial Intelligence Machine Learning?

A Summer Artificial Intelligence (AI) Machine Learning (ML) job is a temporary internship or position, typically offered to students or recent graduates during the summer months, that focuses on working with AI and ML technologies. In these roles, participants gain hands-on experience by collaborating on projects involving data analysis, developing machine learning models, and implementing AI algorithms. These positions are designed to help individuals build practical skills, expand their technical knowledge, and explore potential career paths in the rapidly growing field of AI and ML.

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

AspectSummer Artificial Intelligence Machine LearningSummer Data Science
Required CredentialsBachelor's or Master's in CS, AI, ML, or related fieldsBachelor's or Master's in CS, Data Science, Statistics, or related fields
Work EnvironmentResearch labs, tech companies, startupsData analysis teams, consulting firms, tech companies
Industry UsageDeveloping AI models, ML algorithms, automationData analysis, visualization, business insights
Common Search/ComparisonYesYes

Summer Artificial Intelligence Machine Learning focuses on developing AI systems and algorithms, often involving programming and model training. Summer Data Science emphasizes analyzing and interpreting data to generate insights. While both roles require strong technical skills and similar educational backgrounds, AI/ML roles are more research and development-oriented, whereas Data Science roles focus on data analysis and visualization.

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 Summer Artificial Intelligence Machine Learning jobs in California look for? The top searched job categories for Summer Artificial Intelligence Machine Learning jobs in California are:

Hybrid Visiting of Artificial Intelligence

devry

San Jose, CA • On-site

Full-time

Re-posted 18 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.