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Applied Machine Learning Intern Jobs in Austin, TX

Machine Learning Scientists III Within the AI & Data organization, the Marketplace Science team develops, optimizes and operationalizes applied science driven marketplace levers that support a ...

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and ...

Showing results 41-60

Applied Machine Learning Intern information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

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

As of Sep 4, 2026, the average yearly pay for applied machine learning intern in Austin, TX is $42,209.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,200.00 and $45,600.00 per year, depending on experience, location, and employer.

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

AspectApplied Machine Learning InternData Science Intern
Required SkillsMachine learning algorithms, programming (Python, R), data analysisStatistical analysis, data visualization, programming (Python, R)
Work EnvironmentDeveloping ML models, experimenting with algorithms, deploying modelsData cleaning, analysis, reporting insights
Industry UsageTech companies, AI startups, research labsBusiness analytics, market research, finance

Applied Machine Learning Interns focus on developing and deploying machine learning models, requiring knowledge of algorithms and programming. Data Science Interns typically handle data analysis, visualization, and reporting. While both roles involve data skills, applied ML interns work more on model implementation, whereas data science interns focus on insights and data interpretation.

What job categories do people searching Applied Machine Learning Intern jobs in Austin, TX look for?

The top searched job categories for Applied Machine Learning Intern jobs in Austin, TX are:

What cities near Austin, TX are hiring for Applied Machine Learning Intern jobs?

Cities near Austin, TX with the most Applied Machine Learning Intern job openings:

Infographic showing various Applied Machine Learning Intern job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $42,209 per year, or $20.3 per hour.

Quantitative Research Intern, PhD (Summer 2027)

Optiver

Austin, TX • On-site

Full-time, Temporary, Internship

Re-posted 4 days ago


Job description

As a Quantitative Research Intern, you'll work alongside researchers, engineers, and traders to tackle some of the most challenging quantitative problems in global financial markets. You'll analyze large-scale datasets, develop predictive models and algorithms, and apply statistical and machine learning techniques to uncover patterns in market behavior. AI-driven research at Optiver is where competitive advantage is built, transforming ideas, models, and insights into trading strategies that operate in live markets.
This opportunity is also available in our Chicago office.
What You'll Do:
Led by our dedicated Education team, you'll build a strong foundation in market structure and options theory. This internship follows an apprentice-style learning model where you'll work alongside an experienced researcher and contribute to a project that's aligned with current business needs. Throughout the internship, you'll gain exposure to the AI tools and technologies that support research and development across the business, with the opportunity to contribute to several key areas:
  • Develop predictive models and machine learning systems to better understand market behavior and identify trading opportunities
  • Analyze large-scale market and order-flow data to uncover signals, evaluate hypotheses, and improve trading performance
  • Build and test statistical and stochastic models for pricing, forecasting, and risk management
  • Apply modern research techniques, including deep learning and AI-enabled workflows, to accelerate discovery and improve research efficiency

What You'll Get:
You'll join a culture of collaboration, continuous improvement, and excellence, surrounded by curious thinkers and creative problem-solvers. Together, you'll tackle some of the toughest challenges in the financial markets by leveraging cutting-edge machine learning research to develop innovative, real-world solutions.
In addition, you'll receive:
  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • The opportunity to earn a return internship or full-time offer in Chicago, Austin, or New York City based on performance
  • A highly-competitive internship compensation package
  • Optiver-covered flights, living accommodations, and commuting stipends
  • Extensive office perks, including breakfast, lunch, snacks, regular social events, clubs, sporting leagues, and more

What To Expect:
As part of our assessment process, you may be invited to participate in a multi-day, on-site evaluative program. Through hands-on workshops, technical discussions, and direct exposure to our researchers and traders, you'll gain insight into how research is applied at Optiver and how PhD students transition successfully into industry. Attendance and successful completion of this program may be required to receive an internship offer.
Who You Are:
  • Currently enrolled in a PhD program in Statistics, Computer Science, Machine Learning, Mathematics, or a related STEM field with outstanding academic performance
  • Expected graduation between December 2027 - June 2029 and available to intern during Summer 2027
  • Open to full-time opportunities upon graduation in 2028 or 2029
  • Solid foundation in mathematics, probability, and statistics
  • Excellent research, analytical, and modeling skills
  • Experience applying machine learning methods to real-world research problems, such as time-series analysis, prediction, forecasting, pattern recognition, optimization, or decision-making
  • Proficiency in any programming language
  • Strong interest in working in a fast-paced, collaborative environment
  • Fluent in English with strong written and verbal communication skills

Who We Are:
Optiver is a leading technology- and research-driven trading firm. Our teams of scientists, engineers, mathematicians, and traders work side by side to develop, test, and scale ideas that shape how we understand and trade global markets. Powered by a global platform built for rapid experimentation and iteration, we combine the scientific rigor of a research institution with the pace of a technology company.
Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.
Optiver is supportive of US immigration sponsorship for this role.
*Optiver has a global application re-apply policy for our intern and graduate roles. If you have completed an online assessment or interviewed for a quantitative graduate or internship role at any Optiver location in the past 8 months, please note that you are not yet eligible to reapply. We welcome you to re-apply to after the 8-month cool off period.