1

Machine Learning Summer Internship Jobs in California

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company ... Data analysis and machine learning pipelines * AI agents, retrieval systems, and evaluation ...

Showing results 21-40

Machine Learning Summer Internship information

See California salary details

$25.2K

$42K

$86.8K

How much do machine learning summer internship jobs pay per year?

As of Aug 14, 2026, the average yearly pay for machine learning summer internship 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 a machine learning summer intern, and why are they important?

To thrive as a Machine Learning Summer Intern, you need a solid background in mathematics, statistics, and programming (especially Python), often supported by ongoing coursework in computer science or related fields. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems such as Git, and data analysis tools is typically required. Strong problem-solving skills, curiosity, and teamwork are important soft skills that help interns contribute effectively and learn quickly. These skills and qualities are crucial for applying theoretical knowledge, collaborating on real projects, and adapting to the fast-evolving field of machine learning.

What types of projects can I expect to work on during a machine learning summer internship?

As a Machine Learning Summer Intern, you can expect to contribute to projects such as data preprocessing, building and evaluating machine learning models, and assisting with the deployment of algorithms into production environments. Interns often work alongside data scientists and engineers on real-world datasets to solve business problems, develop prototypes, or improve existing models. This hands-on experience will help you gain practical skills in using popular ML frameworks and understanding the end-to-end machine learning workflow.

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

AspectMachine Learning Summer InternshipData Science Summer Internship
Required CredentialsBasic programming, math, and machine learning knowledgeProgramming, statistics, and data analysis skills
Work EnvironmentDeveloping ML models, algorithms, and prototypesData analysis, visualization, and reporting
Industry UsageTech companies, AI startups, research labsBusiness, finance, healthcare, tech firms

Both internships involve working with data and require programming skills, but Machine Learning Summer Internships focus on developing algorithms and models, while Data Science Summer Internships emphasize data analysis and insights. The choice depends on your interest in building models versus analyzing data.

What is a machine learning summer internship?

A Machine Learning Summer Internship is a temporary, typically 8-12 week program for students or recent graduates to gain practical experience in machine learning. Interns work under the supervision of experienced professionals, contributing to real-world projects involving data analysis, model development, and algorithm implementation. These internships often provide mentorship, networking opportunities, and exposure to the latest tools and technologies in the field. They are valuable for building technical skills and improving career prospects in artificial intelligence and data science.

What are the most commonly searched types of Machine Learning Summer jobs in California?

The most popular types of Machine Learning Summer jobs in California are:

What job categories do people searching Machine Learning Summer Internship jobs in California look for?

The top searched job categories for Machine Learning Summer Internship jobs in California are:

What cities in California are hiring for Machine Learning Summer Internship jobs?

Cities in California with the most Machine Learning Summer Internship job openings:

Infographic showing various Machine Learning Summer Internship job openings in California as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $42,026 per year, or $20.2 per hour.

Applied Data Science Intern

Evolver

Palo Alto, CA

Full-time, Internship

Re-posted 25 days ago


Job description

Applied Data Science Summer Internship 

About Us:

Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In just 1.5 years, the company has grown from 0 to nearly 100 employees, bringing together an exceptional team of technologists, researchers, and industry experts. Founders includes former executives from some of the world's top organizations, including the former Global CTO and Global Board Member of Ernst and Young and the former VP of AI from Microsoft, alongside senior leaders from other major global enterprises. The team includes multiple PhDs and a strong concentration of employees with advanced degrees from leading universities. This in-person internship offers a small cohort of students the opportunity to work directly alongside experienced operators and AI experts while gaining hands-on exposure to using the latest innovations in data science applications at a frontier startup environment.

Program Details:

Evolver is launching a small, highly selective summer internship cohort for students and emerging talent to gain hands-on experience applying data science techniques to enterprise datasets while learning to leverage and deploy AI systems for real-world Fortune 500 business use cases.

This is an intensive 10-week, full-time small cohort program designed to provide direct mentorship from experienced professionals in computer science, data science, artificial intelligence, and enterprise software deployment.

  • Duration: 10 weeks (full-time), June through Early August.
  • Competitive Compensation: Tailored to your experience and skill set.
  • Format: Hybrid (4+ days in person) - Based in Palo Alto, CA off University Ave
  • Cohort Size: Small and mentorship-focused
  • Learning Goals: Develop and apply AI-driven data science solutions on real-world datasets and workflows supporting Fortune 500 enterprise use cases.

Role Details:

Interns will contribute to real data innovation projects involving:

  • Data analysis and machine learning pipelines
  • AI agents, retrieval systems, and evaluation frameworks
  • Enterprise AI integration and deployment tooling
  • Product prototyping and applied research
  • Automation systems for large-scale organizational use
  • Real world enterprise use cases of graph theory
  • Gain direct exposure to Fortune 500 clients
  • Access enterprise-scale AI and data science initiatives through hands-on collaboration with internal teams and customer engagements.

Projects are oriented toward practical AI solutions deployed in enterprise and Fortune 500 environments.

Mentorship & Learning

Interns will work closely with experienced staff and technical mentors with expertise in:

  • Computer Science
  • Data Science & Analytics
  • Applied AI & Machine Learning
  • Enterprise Infrastructure
  • Scalable AI Deployment
  • Risk and Compliance Frameworks
  • Tax and Audit

The program is structured as a high-engagement cohort-based apprenticeship experience emphasizing:

  • Daily in person technical collaboration
  • Rapid learning and iteration
  • Exposure to real deployment challenges
  • Cross-disciplinary problem solving
  • Professional development in AI engineering and enterprise systems

Who Should Apply:

We welcome applications from:

  • Graduate students with a record of excellence
  • Exceptional advanced undergraduates

All candidates are required to be recommended by an accredited professor leading a relevant program at a top university. Will be verified during application process.

Strong candidates typically demonstrate:

  • Programming experience
  • Curiosity about AI systems and emerging technologies
  • Initiative, creativity, and strong problem-solving ability
  • Prior technical, research, or project experience

You do not need deep expertise in every area, we value intellectual curiosity, adaptability, and motivation to build.