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Machine Learning Research Intern Jobs in Austin, TX

webAI

AI Research Scientist

Austin, TX · On-site

The AI Research Scientist will design, train, evaluate, and optimize cutting-edge machine learning models, collaborating with various teams to ensure innovations have real-world impact.

Avride

Machine Learning Engineer

Austin, TX · On-site

Work closely with researchers, software engineers, and robotics experts to integrate machine learning solutions into real-world autonomous systems. Qualifications : Required : • Strong ...

Neuralink

Machine Learning Engineer

Austin, TX · On-site

$199K - $331K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Formulate research questions to guide the development of neural networks and signal processing ... for machine learning applications for BCI. * Lead the team by performing at a high standard ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

  • Medical

... research and experimentation to advance machine learning capabilities Collaborate with cross-functional teams to integrate AI solutions into production environments Analyze large datasets to extract ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

  • Medical

... research and experimentation to advance machine learning capabilities • Collaborate with cross-functional teams to integrate AI solutions into production environments • Analyze large datasets to ...

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All JobsMachine Learning Research Intern JobsMachine Learning Research Intern Jobs in Austin, TX

Machine Learning Research Intern information

See Austin, TX salary details

$25.3K

$42.2K

$87.2K

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

As of Aug 15, 2026, the average yearly pay for machine learning research 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 are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.

What are popular job titles related to Machine Learning Research Intern jobs in Austin, TX?

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

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

Machine Learning Research Intern jobs near you
Infographic showing various Machine Learning Research Intern job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% 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 14 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.

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