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Machine Learning Intern Jobs in Santa Ana, CA (NOW HIRING)

A key focus of this role will be creating engaging training content, including training videos, scripts, presentations, and other learning materials. The intern will work closely with HR and ...

A key focus of this role will be creating engaging training content, including training videos, scripts, presentations, and other learning materials. The intern will work closely with HR and ...

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Machine Learning Intern information

See Santa Ana, CA salary details

$26.5K

$44.3K

$91.6K

How much do machine learning intern jobs pay per year?

As of Sep 4, 2026, the average yearly pay for machine learning intern in Santa Ana, CA is $44,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,800.00 and $47,900.00 per year, depending on experience, location, and employer.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

What are the key skills and qualifications needed to thrive as a machine learning intern, and why are they important?

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

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

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What are the most commonly searched types of Machine Learning jobs in Santa Ana, CA?

The most popular types of Machine Learning jobs in Santa Ana, CA are:

What job categories do people searching Machine Learning Intern jobs in Santa Ana, CA look for?

The top searched job categories for Machine Learning Intern jobs in Santa Ana, CA are:

What cities near Santa Ana, CA are hiring for Machine Learning Intern jobs?

Cities near Santa Ana, CA with the most Machine Learning Intern job openings:

Infographic showing various Machine Learning Intern job openings in Santa Ana, CA as of August 2026, with employment types broken down into 1% As Needed, 65% Full Time, 25% Part Time, 1% Temporary, and 8% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $44,312 per year, or $21.3 per hour.

Additive Engineering Intern (Summer 2027)

Freeform

Los Angeles, CA โ€ข On-site

$35/hr

Temporary, Internship

Posted 10 days ago


Job description

ADDITIVE ENGINEERING INTERN (SUMMER 2027)
Freeform builds AI-native manufacturing systems that unify software, hardware, and physics to produce industrial-scale parts at the speed of human ideation. By treating manufacturing as a single integrated system, we unlock a new era of innovation where complex hardware is designed, built, and scaled without limits.
As an Additive Engineering Intern at Freeform, you will contribute to the development and scaling of our advanced metal 3D printing processes, including design for additive manufacturing (DFAM) feedback, print file preparation, toolpath automation, part quality analysis, and end-to-end process improvement. You will work closely with mechanical, electrical, software, and manufacturing engineers to support all stages of print development for high-volume production. Interns at Freeform own meaningful cradle-to-grave projects. Using first-principles thinking, you will help define test methods, evaluate solutions, iterate quickly, and synthesize information from engineering drawings, in-situ machine data, post-processing results, and inspection data to draw conclusions that improve printing and downstream machining processes.
3D printing experience is not required to be successful here - we look for smart, motivated, collaborative engineers who love solving hard problems and creating amazing technology!
Responsibilities:
  • Own a cradle to grave project that delivers meaningful impact to critical print factory capabilities or customer print workflows
  • Support all stages of print development including design for additive manufacturing feedback, file preparation, printing, post-processing, and quality control
  • Analyze in-situ data and post-print part quality to drive continuous improvement in system performance
  • Use first-principles thinking to define problems, develop test methods, evaluate solutions, iterate, and provide technical recommendations

Basic Qualifications:
  • Currently enrolled in a bachelor's degree in mechanical or aerospace engineering from an ABET accredited university or college
  • Hands on design experience from internships or engineering clubs such as FSAE, Baja SAE, solar car, rocket club, robotics club, or similar
  • Strong grasp of mechanical engineering fundamentals and comfortable taking a first-principles approach to solving problems

Nice to Have:
  • Advanced degree (Master's, PhD) in mechanical or aerospace engineering
  • Experience with metal 3D printing or additive manufacturing processes
  • Experience with process development for metal additive manufacturing
  • Scripting experience in MATLAB or similar tools for toolpath generation
  • Experience with DFM and GD&T
  • Experience with CNC machining
  • Passion for improving the state of metal 3D printing
  • Comfortable working in fast-paced, ambiguous environments and iterating quickly (comfortable building the plane as we fly it)
  • Strong communicator who collaborates across disciplines and proactively seeks support when needed
  • Willing to take ownership of tasks big and small, with a hands-on, problem-solving mindset
  • Strong work ethic with a refuse-to-fail mindset
  • Demonstrated indicators of excellence and/or achieving success against adversity (i.e. top academic performance, leadership in engineering clubs, first-generation college student, or other examples of resilience and achievement)

Location:
  • Based in Hawthorne, our vertically integrated facility brings technology development, R&D, and production together under one roof. We operate at the center of LA's deep tech ecosystem, surrounded by some of the most ambitious hardware innovation happening anywhere in the country.

What We Offer:
  • We have an inclusive and diverse culture that values collaboration, learning, and making deliberate data-driven decisions
  • We offer a unique opportunity to be an early and integral member of a rapidly growing company that is scaling a world-changing technology
  • Compensation and Benefits
    • The compensation for this role:
      • Engineering Intern/Undergraduate: $30/hour
      • Engineering Intern/Masters: $32.50/hour
      • Engineering Intern/PhD: $35/hour
    • Relocation assistance provided
    • Free daily catered lunch and dinner, and fully stocked kitchenette
    • Casual dress, flexible work hours, and regular catered team building events
  • Freeform is an Equal Opportunity Employer that values diversity; employment with Freeform is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other legally protected status.