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Artificial Intelligence Machine Learning Physics 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 ...

Machine Learning Physics Graduate Student

Livermore, CA · On-site

$6.7K - $8.2K/mo

  • Retirement

We have multiple openings for Machine Learning Graduate Student Interns to engage in practical ... These positions are in in the Equation of State Materials Theory Group of the Physics Division of ...

Masters in Artificial intelligence, Machine Learning, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering or related field. Preferred ...

Sr. Machine Learning Engineer

Santa Clara, CA

$175K - $263K/yr

  • Medical

  • Dental

  • Retirement

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 Physics information

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning physicist, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Physicist, you need a strong background in physics, advanced mathematics, computer science, and experience with machine learning algorithms, typically supported by a graduate degree in a related field. Proficiency in programming languages such as Python or C++, machine learning frameworks like TensorFlow or PyTorch, and familiarity with data analysis tools are essential, along with experience in scientific computing. Critical thinking, problem-solving, and strong communication skills help you interpret complex data, collaborate across disciplines, and convey research findings effectively. These combined skills are crucial for developing innovative AI models, driving scientific discovery, and advancing technology at the intersection of physics and machine learning.

What is artificial intelligence machine learning physics?

Artificial Intelligence Machine Learning Physics is an interdisciplinary field that applies AI and machine learning techniques to solve complex problems in physics. Experts in this area use algorithms to analyze large datasets, model physical phenomena, and accelerate scientific discoveries. The field combines knowledge of physics, computer science, and mathematics to design models that can predict, simulate, or interpret physical processes. Applications include materials science, quantum mechanics, astrophysics, and more, making it a rapidly growing area of research and industry.

What collaborative projects can professionals in artificial intelligence machine learning physics expect to work on?

Professionals in Artificial Intelligence Machine Learning Physics often work on interdisciplinary teams, partnering closely with data scientists, physicists, and software engineers. They may contribute to projects such as developing advanced simulation tools, optimizing experimental data analysis, or creating machine learning models to predict physical phenomena. Collaboration is key, as these roles frequently involve integrating AI algorithms with physical models and leveraging domain-specific knowledge from physics experts. This dynamic environment fosters continual learning and offers opportunities to lead innovative research or transition into specialized engineering and research leadership roles.

What is the difference between Artificial Intelligence Machine Learning Physics vs Data Scientist?

AspectArtificial Intelligence Machine Learning PhysicsData Scientist
Required credentialsDegree in Computer Science, Physics, or related fields; certifications in AI/MLDegree in Statistics, Mathematics, Computer Science; certifications in data analysis
Work environmentResearch labs, tech companies, academia focusing on AI/ML applications in physicsBusiness, finance, healthcare sectors analyzing large datasets
Industry usageDeveloping AI models for physics simulations, research, and technologyExtracting insights from data to inform business decisions

Artificial Intelligence Machine Learning Physics and Data Scientist roles share a focus on data analysis and technical skills. However, AI/ML Physics emphasizes developing algorithms within physics contexts, while Data Scientists focus on analyzing diverse datasets across industries. Both roles often require similar educational backgrounds and certifications, but their applications and work environments differ significantly.

What job categories do people searching Artificial Intelligence Machine Learning Physics jobs in California look for?

The top searched job categories for Artificial Intelligence Machine Learning Physics jobs in California are:

What cities in California are hiring for Artificial Intelligence Machine Learning Physics jobs?

Cities in California with the most Artificial Intelligence Machine Learning Physics job openings:

Hybrid Visiting of Artificial Intelligence

devry

San Jose, CA • On-site

Full-time

Re-posted 22 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.