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Machine Learning Professor Jobs in California (NOW HIRING)

Voltai

Machine Learning Engineer

Palo Alto, CA · On-site

We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of ...

Voltai, Inc

Machine Learning Engineer

Palo Alto, CA · On-site

We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of ...

Voltai, Inc

Machine Learning Engineer

Palo Alto, CA

We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of ...

Matroid

Deep Learning Field Engineer

Palo Alto, CA · Hybrid

Founded in 2016 by a Stanford professor, Matroid has raised $33.5 million from NEA, Energize ... Experience training and deploying state-of-the-art CV models using popular machine learning ...

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Machine Learning Professor information

What are the key skills and qualifications needed to thrive as a Machine Learning Professor, and why are they important?

To thrive as a Machine Learning Professor, you need deep expertise in machine learning algorithms, mathematics, and data science, typically supported by a Ph.D. in computer science or a related field. Familiarity with programming languages like Python and R, as well as tools such as TensorFlow, PyTorch, and academic research platforms, is essential. Exceptional communication, mentorship abilities, and enthusiasm for teaching help inspire and guide students and peers. These skills ensure effective research output, high-quality teaching, and the development of future leaders in the field.

How does a Machine Learning Professor typically balance research, teaching, and mentorship responsibilities?

Machine Learning Professors usually split their time between conducting original research, teaching undergraduate and graduate courses, and mentoring students. Balancing these responsibilities can be challenging, particularly when managing multiple research projects and supervising student theses. Professors often collaborate with industry partners and other academic departments, which enhances research opportunities but also adds to their workload. Effective time management and prioritization are key to thriving in this dynamic environment, and universities often provide some flexibility in teaching loads or research support to help maintain this balance.

What does a Machine Learning Professor do?

A Machine Learning Professor teaches university-level courses on machine learning, data science, and related topics. They conduct original research in the field, often publishing their findings in academic journals and presenting at conferences. In addition to lecturing, they mentor students, supervise theses or dissertations, and may collaborate with industry partners on research projects. Their work helps advance the understanding and applications of machine learning.
What cities in California are hiring for Machine Learning Professor jobs? Cities in California with the most Machine Learning Professor job openings:
Machine Learning Professor jobs near you
Infographic showing various Machine Learning Professor job openings in California as of May 2026, with employment types broken down into 1% As Needed, 76% Full Time, and 23% Part Time. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Machine Learning Engineer

Voltai

Palo Alto, CA • On-site

Full-time

Posted 23 days ago

Job description

About Voltai
Voltai is developing world models, and agents to learn, evaluate, plan, experiment, and interact with the physical world. We are starting out with understanding and building hardware; electronics systems and semiconductors where AI can design and create beyond human cognitive limits.

About the Team

Backed by Silicon Valley’s top investors, Stanford University, and CEOs/Presidents of Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL researchers, Olympiad medalists (IPhO, IOI, etc.), CTOs of Synopsys & GlobalFoundries, Head of Sales & CRO of Cadence, former US Secretary of Defense, National Security Advisor, and Senior Foreign-Policy Advisor to four US presidents.

What we're Looking For

  • Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics programs.

  • Proven track record of delivering AI/ML projects from concept to production.

  • Hands-on experience fine-tuning and deploying large language models (LLMs) in production environments.

  • Prior experience working with multi-modal models (e.g., combining text, image, or audio inputs).

Bonus Points

  • Background in competitive programming.

  • Contributions to open-source initiatives.

  • Notable awards or publications in leading journals/conferences.

  • Experience thriving in a fast-paced, hyper-growth startup environment.