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Machine Learning Engineer Intern Jobs in California

Machine Learning & NLP: Solid understanding of Large Language Models (LLMs), natural language processing, and prompt engineering. * Python Programming: Strong proficiency in Python for machine ...

Strong foundation in classification and supervised learning. > Preferred Skills: Nice-to-Haves * Experience with distributed processing (e.g., Spark or Ray). Understanding of autonomous driving ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Machine Learning Engineer Location: Fremont, CA Duration: 12+ Months Tesla/ $65 About the Role Our direct client is seeking a highly skilled Machine Learning Engineer to join their Software Machine ...

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Machine Learning Engineer Intern information

See California salary details

$25.2K

$42K

$86.8K

How much do machine learning engineer intern jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning engineer intern 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 types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in California? The most popular types of Machine Learning Engineer jobs in California are:
What job categories do people searching Machine Learning Engineer Intern jobs in California look for? The top searched job categories for Machine Learning Engineer Intern jobs in California are:
What cities in California are hiring for Machine Learning Engineer Intern jobs? Cities in California with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in California as of May 2026, with employment types broken down into 6% Internship, 67% Full Time, 21% Part Time, and 6% Contract. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution, with an average salary of $42,026 per year, or $20.2 per hour.
Machine Learning Engineer Intern

Machine Learning Engineer Intern

Neuralink

South San Francisco, CA

$35/hr

Other

Posted 24 days ago


Job description

Team Description:

The Brain Computer Interface (BCI) Applications Team is responsible for delivering a product that gives people with paralysis the ability to control computers, phones, gaming consoles, and robotic arms with their minds at the same speed and functionality level as able-bodied people can. Furthermore, the team is focused on restoring speech for mute individuals and enabling direct, natural silent communication with AI agents.  In this role, you'll work with neuroscientists, physicians, software engineers, and electrical engineers to develop the next-generation human-ready Brain-Computer Interface (BCI). 

Job Description and Responsibilities:

We are hiring a Machine Learning Engineer Intern to develop novel neural decoders to increase control speed and accuracy, improve reliability, and expand functionality of BCIs. You will play a critical role in developing machine learning solutions and driving the successful execution of projects to achieve mission critical goals. You'll work with cross-functional teams to design new BCI functionalities and novel computer user interfaces.

Required Qualifications:

  • Evidence in delivering high-impact projects either in academia or industry
  • Prior experience designing and building Machine Learning models
  • Deep understanding of machine learning concepts and fundamentals
  • Experience in analyzing complex datasets, driving insights, and communicating results in a simple and clear way to both technical and non-technical stakeholders
  • Excellent communication and collaboration skills
  • Strong coding skills, with a focus on clean, efficient, and scalable code development

Preferred Qualifications:

  • Experience working with time series or unstructured data

Expected Compensation:

The anticipated hourly rate for this position is listed below.

California Hourly Rate: 
$35/Hr USD