ZipRecruiter

Log In

1

Phd Machine Learning Jobs in California (NOW HIRING)

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

As part of our machine learning team, you will play a vital role in prototyping foundational ... Preferred Qualifications MS/PhD in computer vision, electrical, optical or computer engineering or ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Preferred Qualifications MS or PhD in computer vision, computer graphics, machine learning, computer science, computer engineering or related fields. Self-motivated with proven ability to effectively ...

Apple

Machine Learning Engineer, Proactive

Cupertino, CA · On-site

... PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. At least 2 years of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more ...

Apple

Machine Learning Engineer, Proactive

Cupertino, CA

$150K - $277K/yr

... PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. At least 2 years of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$150K - $277K/yr

As part of our machine learning team, you will play a vital role in prototyping foundational ... Preferred Qualifications MS/PhD in computer vision, electrical, optical or computer engineering or ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

About the Role At Poesis, machine learning and artificial intelligence open the door to improved ... Skill leveraging Claude Code, Codex, or other coding agents * BS/MS/PhD in Computer Science or a ...

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

Minimum of 3 years of experience in machine learning, with demonstrated application to real-world problems; 1 year of machine learning experience with a PhD. * Strong foundation in supervised and ...

Qualcomm

Machine Learning Researcher

San Diego, CA · On-site

OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field. • 6+ months of academic and/or work experience developing and/or optimizing machine learning models ...

next page

Showing results 1-20

All JobsPhd Machine Learning JobsPhd Machine Learning Jobs in California

Phd Machine Learning information

See California salary details

$13

$22

$30

How much do phd machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for phd machine learning in California is $22.52, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $25.14 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional, and why are they important?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

What is the difference between Phd Machine Learning vs Data Scientist?

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities in California are hiring for Phd Machine Learning jobs? Cities in California with the most Phd Machine Learning job openings:
Phd Machine Learning jobs near you
Infographic showing various Phd Machine Learning job openings in California as of July 2026, with employment types broken down into 12% Internship, 64% Full Time, 6% Part Time, 12% Contract, and 6% Nights. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $46,846 per year, or $22.5 per hour.

Research Intern (PhD), Machine Learning

Output Biosciences

San Francisco, CA • On-site

Full-time

Medical, Dental, Vision

Re-posted 8 days ago

Job description

Output has built a biological reasoning model that understands biology at the scale and complexity life actually operates. Our model independently learned the principles of molecular interactions, opening up drug treatments that were previously impossible. We're already generating therapies that traditional approaches cannot reach. The hardest problems in both AI and biology are being solved here, and there is room for you to own one.

Output is currently in stealth, operated by a team of repeat founders and biotech veterans with multiple exits in AI x Bio, and backed by top-tier VCs including Y Combinator.

Our internships offer flexible commitment, with a minimum of 20 hours per week, ranging 12 to 24 weeks. We have various start dates available to accommodate your academic schedule. There may be opportunities for full-time employment upon successful completion of your PhD.


The Role

You will own a research project that directly advances Output's research and its path to new therapies. This is not a side project: your work will contribute to the same models and methods the full-time team builds on. We will select a project together based on your research interests and our priorities, with a path to publishing your work at top-tier venues and the opportunity to continue with additional projects throughout the year.


About You

  • You are currently pursuing a PhD in machine learning, computer science, computational biology, physics, mathematics, or a related field

  • You have a strong research track record, demonstrated by publications or submitted work at venues such as NeurIPS, ICML, ICLR, or relevant computational biology conferences

  • You have hands-on experience designing and running ML experiments, including training models and analyzing results

  • You are proficient in Python and PyTorch, and comfortable working with large-scale datasets and GPU infrastructure

  • You can work independently on a research problem: scoping an approach, running experiments, interpreting results, and communicating findings clearly

Bonus Points

  • You have experience applying machine learning to biological, chemical, or molecular data

  • You have a background in computational biology, biophysics, chemistry, or a related natural science

  • You have experience with generative models, representation learning, or self-supervised learning

  • You have contributed to open-source machine learning or computational biology projects

Our Values

❤️ Heart: We foster a culture of ownership. We are assembling a team of individuals who are passionate and take pride in their contributions.

🏆 Excellence: We have an unwavering commitment to excellence and continuously challenge ourselves to reach the highest standards.

🚀 Practicality: We value practicality and results-oriented thinking. We are committed to making a tangible impact on the lives of patients and the broader community.

📣 Honesty: We place a high value on honesty and directness. We firmly believe in addressing issues as they arise, in an open and transparent manner.

🎮 Fun: We believe that life is too short to not have fun. Our goal is to create a workplace that is fun, engaging, rewarding and fulfilling.

What We Offer

  • We encourage new and different ideas, creativity and contrarian thinking

  • Healthy feedback focused environment to help you strive - leadership will have high expectations, regularly share constructive feedback, support you and help you grow, and welcome receiving feedback and ideas from you

  • You own your day-to-day management. What we care about is that we all hit our milestones

  • Competitive salary and equity in a growing, well-funded startup

  • Excellent medical, dental, and vision coverage