1

Machine Learning Intern Jobs in California (NOW HIRING)

POSITION SUMMARY As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer ...

Develop and improve machine learning models for Ads ranking and recommendation systems * Design and build features for ranking algorithms using large-scale datasets * Process and analyze billions of ...

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 ...

next page

Showing results 1-20

Machine Learning Intern information

See California salary details

$25.2K

$42K

$86.8K

How much do machine learning intern jobs pay per year?

As of May 29, 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.

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 cities in California are hiring for Machine Learning Intern jobs? Cities in California with the most Machine Learning Intern job openings:
Machine Learning Intern

Machine Learning Intern

EarnIn

Mountain View, CA • Hybrid

$40/hr

Other

Posted 20 days ago


Job description

POSITION SUMMARY

As a Fintech company where Machine Learning (ML) is one of the key drivers of growth, our operations highly rely on machine learning models, from business decisions to customer experiences. Therefore, building and deploying state-of-the-art machine learning systems to drive impact via our data capabilities is key. To guarantee the success of machine learning systems, we need to provide a detailed formulation, extensive experimentation, and to transform ML models into high-performance production-level code, including not only implementing sophisticated machine learning algorithms but also robustness monitoring and system logging/alarming. 

 We seek talented and motivated students and recent graduates with a strong background in machine learning, deep learning, language models and generative AI, programming, and data analysis to join our 12-week Machine Learning Internship Program. You will work on real-world projects, collaborate with experienced professionals, gain valuable experience in the fintech industry, and realize business and social impact. This role requires hybrid work from our Mountain View office, with 2 days a week in person. This internship will pay $40 per hour, with an expected 40 hours per week for the 12-week program. We are unable to provide visa sponsorship or immigration support for this position.  

WHAT YOU'LL DO 

  • Train and fine-tune large-scale Foundation Models to support various fintech product use cases
  • Work with a large dataset, including structured and unstructured data
  • Help in ensuring improvements in our current ML systems via model, data, or experimentation upgrades
  • Gain hands-on experience with a wide array of technologies, including PyTorch, AWS, Kafka, Databricks, etc

WHAT WE'RE LOOKING FOR

  • Actively pursuing a Master's or PhD in Computer Science, Information Technology, or a related field
  • Located in Mountain View, or have the ability to relocate there, for the duration of the internship 
  • Strong understanding of statistical models, familiarity, and in-depth understanding of machine learning and deep learning algorithms. Familiarity with training or fine-tuning large-scale models, Sequence Transformer models 
  • Interest in multimodal or multitask learning across structured, sequential, and behavioral data
  • Familiarity with AI tools, harness engineering, agentic workflow, etc.
  • Hands-on programming experience in Python and ML frameworks such as PyTorch
  • Equipped with good verbal and written communication skills
  • A background demonstrating strong problem-solving skills
  • Committed to taking ownership of projects, conducting thorough investigations, and driving initiatives to conclusion

#LI-Hybrid