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Internship Machine Learning Quant Jobs in Milpitas, CA

Crowe LLP

Machine Learning Intern

San Jose, CA · On-site

$27 - $42/hr

DS interns will have a designated data scientist mentor and will spend the majority of their time working on a data science project overseen by that mentor. The expectation is that at the end of the ...

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All JobsMachine Learning Quant JobsInternship Machine Learning Quant JobsInternship Machine Learning Quant Jobs in Milpitas, CA

Internship Machine Learning Quant information

See Milpitas, CA salary details

$29.7K

$49.6K

$102.6K

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

As of Aug 25, 2026, the average yearly pay for internship machine learning quant in Milpitas, CA is $49,626.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,900.00 and $53,600.00 per year, depending on experience, location, and employer.

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

What job categories do people searching Internship Machine Learning Quant jobs in Milpitas, CA look for?

The top searched job categories for Internship Machine Learning Quant jobs in Milpitas, CA are:

What cities near Milpitas, CA are hiring for Internship Machine Learning Quant jobs?

Cities near Milpitas, CA with the most Internship Machine Learning Quant job openings:

Internship Machine Learning Quant jobs near you
Infographic showing various Internship Machine Learning Quant job openings in Milpitas, CA as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $49,626 per year, or $23.9 per hour.

Senior Machine Learning Scientist - Ad Campaign Optimization

Cupertino, CA • On-site

Socket.dev
Network Security • 1 - 10 employees
Learn more about Socket.devexternal

$150 - $230/hr

Other

Posted 8 days ago

Job description

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes—from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. We are seeking a self‑motivated individual that will build out the next generation of our ads platforms and ensure that Apple provides the most relevant and high quality ads experience while maintaining a healthy marketplace. You should have experience developing and implementing machine learning or optimization algorithms, ideally within the ads space, recommendations, or search relevance. You will have an excellent understanding of scalable architectures and thrive working in Agile environments.

Description

In this role, you will design and build scalable solutions that enable advertisers to optimize for their campaign goals and performance on the Apple Ads. You will have the opportunity to build the next generation solutions for budget and bid optimization that enable driving optimal campaign performance and advertiser experience. You will have the opportunity to apply your ability to move the state of the art techniques in a fast growing business that positively impacts publishers, developers and Apple users at global scale. The ability to be a great teammate under tight deadline constraints is key to success.

Minimum Qualifications
  • 5+ years of experience building machine learning and quantitative optimization capabilities across many different product areas at scale
  • Experience in machine learning, quantitative methods, control systems, or reinforcement learning
  • Ability to apply and implement research concepts, ultimately in production quality code
  • Experience defining clear, testable research hypotheses, including intended impact on the business
  • Deep knowledge of design of experiments, online experimentation approaches, preferably at scale
  • Ability to formulate and advocate for R&D objectives and results to cross-functional team members including executive business leadership and product management
  • Experience contributing and/or reviewing research for top conferences and publications
  • Deep fluency in Java or Python
  • Experience with Spark, Hadoop or other distributed frameworks
  • Masters in Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry
Preferred Qualifications
  • Experience in ads optimization, recommendations, or search relevance optimization is highly preferred
  • PhD in Machine Learning, Statistics, Control Theory, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry
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