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Machine Learning Intern Jobs in California (NOW HIRING)

Syntiant

Machine Learning Audio Intern

Redwood City, CA · On-site

Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey ...

PlusAI

Machine Learning Engineer Intern

Santa Clara, CA · On-site

$19 - $65/hr

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

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How much do machine learning intern jobs pay per year?

As of May 31, 2026, the average yearly pay for machine learning 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 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.

More about Machine Learning Intern jobs
What are the most commonly searched types of Machine Learning jobs in California? The most popular types of Machine Learning jobs in California are:
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What job categories do people searching Machine Learning Intern jobs in California look for? The top searched job categories for Machine Learning Intern jobs in California are:
What cities in California are hiring for Machine Learning Intern jobs? Cities in California with the most Machine Learning Intern job openings:
Machine Learning Intern jobs near you
Machine Learning Audio Intern

Machine Learning Audio Intern

Syntiant

Redwood City, CA • On-site

Temporary

Posted 26 days ago

Job description

Summary Description:
Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, is looking for a Machine Learning Audio Intern to take on a critical role to enhance our AI Model for Turkey Gobble Synthesis.
Syntiant Corp. is seeking a turkey gobble detector AED model that runs on NDP chips. It is difficult to collect good quality gobble data due to several logistical issues. As of now, only ~2K samples are available for training such a model. These samples are not enough to train a production quality turkey gobble model.
EcoGen is a neural network model that could generate synthetic but real-sounding bird sounds. It needs only a handful of recordings to synthesize similar sounds. The idea is to leverage this model to get more data for training a better turkey gobble detector AEDmodel. For details on EcoGen, please refer to the hyperlink provided. There are newer models such as BirdDiff, Audio LDM (Text-to-Turkey), Perch 2.0 etc.
Requirements
Specific Duties and Responsibilities:
  • Understanding the model architecture.
  • Running it locally or on the cluster.
  • Fine-tuning the model on the available turkey sounds.
  • Synthesizing real-sounding artificial turkey gobble sounds.
  • Explore better alternatives and pursue them.

Qualifications, Education, and Experience Required:
  • Candidate pursuing a Bachelor's or Master's degree in Computer Science or related field with hands-on experience in AI/ML model training.
  • Industry work experience is not required, but it would be good to have.

Benefits
About Syntiant:
Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering hardware and software solutions for edge AI deployment. The company's purpose-built silicon and hardware-agnostic models are being deployed globally to power edge AI speech, audio, sensor and vision applications across a wide range of consumer and industrial use cases, from earbuds to automobiles. Syntiant's advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient software solutions with proprietary model architectures that enable world-leading inference speed and minimized memory footprint across a broad range of processors. The company is backed by several of the world's leading strategic and financial investors including Intel Capital, Microsoft's M12, Applied Ventures, Bosch Ventures, the Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by visiting www.syntiant.com.

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