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Internship Machine Learning Jobs in California (NOW HIRING)

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120.80K - $159.10K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site

$120.80K - $159.10K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site

$120.80K - $159.10K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Voxelcloud

Machine Learning Engineer

Los Angeles, CA · On-site

We are currently hiring both full-time and interns to join our R&D team. Responsibilities: * Develop deep learning models for prototyping and production purposes according to product feature request

PlusAI

Machine Learning Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

Strong foundation in classification and supervised learning. > Preferred Skills: Nice-to-Haves ... Understanding of autonomous driving problems $19 - $65 an hour Our internship hourly rates are a ...

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Internship Machine Learning information

See California salary details

$25.2K

$42K

$86.8K

How much do internship machine learning jobs pay per year?

As of May 31, 2026, the average yearly pay for internship machine learning in California is $42,026.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,100.00 and $45,400.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Intern, you generally need a solid grounding in mathematics, programming (especially Python), and familiarity with machine learning concepts, often supported by coursework or relevant projects. Experience with tools and libraries like TensorFlow, scikit-learn, and Jupyter Notebooks, as well as knowledge of version control systems like Git, is typically expected. Strong problem-solving skills, willingness to learn, and effective communication set outstanding interns apart. These skills and qualities enable interns to contribute meaningfully to projects, adapt quickly, and collaborate well within technical teams.

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

As a Machine Learning intern, you may work on a variety of projects such as data preprocessing and cleaning, developing and testing machine learning models, or assisting with research experiments. These projects often involve collaborating closely with data scientists and engineers, learning to use popular frameworks like TensorFlow or PyTorch, and presenting your findings to the team. The scope and complexity of your assignments will typically grow as you demonstrate proficiency and initiative, providing valuable real-world experience and networking opportunities.

What are internship machine learning positions?

Internship machine learning positions are temporary roles for students or recent graduates to gain hands-on experience in the field of machine learning. Interns typically work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced professionals. These internships provide valuable exposure to machine learning tools, programming languages such as Python, and industry best practices. They are an excellent way to build technical skills, enhance your resume, and explore career opportunities in artificial intelligence and data science.

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

AspectInternship Machine LearningData Science Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, programming, data analysis basics
Work EnvironmentHands-on ML model development, codingData analysis, visualization, reporting
Industry UsageTech, AI companies, research labsBusiness, finance, healthcare sectors

Internship Machine Learning focuses on developing and implementing machine learning models, requiring programming and ML fundamentals. Data Science Internships involve analyzing data, creating reports, and supporting decision-making. Both roles are common in tech and research industries, but ML internships are more specialized in model building, while Data Science internships emphasize data analysis and visualization.

What are the most commonly searched types of Machine Learning jobs in California? The most popular types of Machine Learning jobs in California are:
What are popular job titles related to Internship Machine Learning jobs in California? For Internship Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Machine Learning jobs in California look for? The top searched job categories for Internship Machine Learning jobs in California are:
What cities in California are hiring for Internship Machine Learning jobs? Cities in California with the most Internship Machine Learning job openings:
Internship Machine Learning jobs near you
Infographic showing various Internship Machine Learning job openings in California as of May 2026, with employment types broken down into 67% Internship, and 33% Full Time. Highlights an 100% In-person job distribution, with an average salary of $42,026 per year, or $20.2 per hour.
Senior Machine Learning Engineer - Healthtech startup

Senior Machine Learning Engineer - Healthtech startup

LaBine and Associates

Palo Alto, CA

$123K - $168.90K/yr

Other

Posted 5 days ago

Job description

In this role you will:

  • Build, deploy, and improve robust machine learning models for product features.

  • Design both offline and online experiments to test ML product features, and perform data-driven analysis on the results to find actionable insights.

  • Provide input and collaborate closely with the ML Infrastructure team towards the development of technical platforms that power ML systems and engineering infrastructure and operations.

  • Mentor ML engineering interns and team members.

  • Source and interview diverse talent to build and grow a strong ML engineering team.

An ideal candidate has:

  • Experience building production machine learning models and systems: Expertise with the full lifecycle of machine learning algorithms in production, including research, deployment, improvements, and maintenance.

  • Ability to translate product intuition into data-driven hypotheses that result in impactful machine learning/engineering solutions.

  • Experience leading cross-functional teams on strategic machine learning product initiatives from conception to successful product outcomes.

  • Demonstrated ability to collaborate with a diverse set of stakeholders such as researchers, business leaders, domain experts (such as doctors), and product managers to solve complex cross-disciplinary problems.

  • Masters with at least 6 years of relevant experience, or BS with at least 8 years of relevant experience.

  • In-depth experience with at least one machine learning framework (such as TensorFlow, PyTorch, etc.)


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About LaBine and Associates

Sourced by ZipRecruiter

LaBine and Associates is a full service talent acquisition firm specializing in executive search for a myriad of industries. Through our partnerships with experienced associates, we can also provide staffing support, expert consultants, and interim executives for your company’s needs. We have deep industry knowledge with understanding in multiple industries. Our specialists include experts in banking/finance, HR/Legal, Technology, Health Care, Life Sciences, Engineering, Energy, Supply Chain, Mining, Agribusiness and manufacturing.

Industry

Professional, scientific, and technical services

Company size

11 - 50 Employees

Headquarters location

San Mateo, CA, US

Year founded

2013

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