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Machine Learning Internship Microsoft Jobs in Georgetown, TX

Hardware Systems Engineering

Austin, TX

$122K - $161K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

Hardware Systems Engineering

Austin, TX

$122K - $161K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

Hardware Systems Engineering

Austin, TX · On-site

$122K - $161K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

Hardware Systems Engineering

Austin, TX

$122K - $161K/yr

MACHINE LEARNING AND AI Within Appleʼs Artificial Intelligence and Machine Learning organization ... Prior internship(s), group or personal project exposure, TA and/or work experience. This posting is ...

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Machine Learning Internship Microsoft information

See Georgetown, TX salary details

$23.7K

$39.6K

$81.8K

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

As of Jul 15, 2026, the average yearly pay for machine learning internship microsoft in Georgetown, TX is $39,565.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,200.00 and $42,700.00 per year, depending on experience, location, and employer.

What is a Machine Learning Internship at Microsoft?

A Machine Learning Internship at Microsoft is a temporary position for students or recent graduates to gain hands-on experience working on real-world machine learning projects. Interns collaborate with experienced engineers and researchers to develop, test, and deploy machine learning models and solutions that impact Microsoft products and services. The internship typically involves working with large datasets, implementing algorithms, and contributing to team goals while learning about cutting-edge AI technologies. Interns also benefit from mentorship, networking opportunities, and exposure to the latest industry practices.

What types of projects do interns typically work on during a Machine Learning Internship at Microsoft?

As a Machine Learning intern at Microsoft, you can expect to work on impactful, real-world projects that contribute to ongoing products or research initiatives. Interns often collaborate with data scientists, software engineers, and product teams to develop, test, and refine machine learning models for applications such as natural language processing, computer vision, or recommendation systems. You'll likely participate in code reviews, present your findings, and receive mentorship from experienced professionals, all within a collaborative and innovative environment. These projects not only enhance technical skills but also provide valuable exposure to large-scale, industry-leading systems.

What is the difference between Machine Learning Internship Microsoft vs Data Science Internship Microsoft?

AspectMachine Learning Internship MicrosoftData Science Internship Microsoft
Required SkillsProgramming, ML algorithms, Python, TensorFlowStatistics, data analysis, Python, SQL
Work EnvironmentResearch and development teams focused on ML modelsData analysis and visualization teams
Industry UsageAI and ML product developmentBusiness insights and data-driven decision making

Both internships are highly competitive roles at Microsoft, often requiring programming skills and relevant coursework. Machine Learning Internships focus on developing and deploying ML models, while Data Science Internships emphasize analyzing data to generate insights. Candidates should review the specific role descriptions to align their skills accordingly.

What are the key skills and qualifications needed to thrive as a Machine Learning Intern at Microsoft, and why are they important?

To thrive as a Machine Learning Intern at Microsoft, you need a solid foundation in mathematics, programming (especially Python), and machine learning concepts, typically supported by coursework or related projects. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and experience using cloud platforms like Azure are often expected. Strong problem-solving skills, curiosity, and effective communication help you collaborate with team members and present findings. These skills are crucial for contributing to innovative projects and translating complex data-driven insights into impactful solutions within a dynamic tech environment.
What job categories do people searching Machine Learning Internship Microsoft jobs in Georgetown, TX look for? The top searched job categories for Machine Learning Internship Microsoft jobs in Georgetown, TX are:
What cities near Georgetown, TX are hiring for Machine Learning Internship Microsoft jobs? Cities near Georgetown, TX with the most Machine Learning Internship Microsoft job openings:

Graduate Quantitative Researcher, PhD (2027 Start)

Optiver

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago


Job description

As a Graduate Quantitative Researcher, you'll tackle some of the most challenging quantitative problems in global financial markets. Working alongside researchers, engineers, and traders, you'll analyze large-scale datasets, develop predictive models and algorithms, and apply statistical and machine learning techniques to better understand market behavior and identify trading opportunities.
Research at Optiver is highly applied and end-to-end. You'll frame research questions, test hypotheses, develop and validate models, and see your ideas evaluated in live market environments. Combining rigorous scientific thinking with modern AI-enabled research infrastructure, you'll transform insights into solutions that directly influence how we trade.
This opportunity is also available in our Chicago office.
What You'll Do:
Your onboarding
You'll participate in Global Optiver Academy, a structure onboarding program for graduates. It gives new joiners a shared foundation in how Optiver trades, builds systems, and manages risk before they move into their teams. As part of your onboarding, you'll gain exposure to the AI tools and technologies that support research and development across the business.
Your responsibilities
As a Quantitative Researcher, you will have 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
  • Highly competitive compensation package
  • Global profit-sharing pool and performance-based bonus structure
  • 401(k) match up to 50%
  • Comprehensive health, mental, dental, vision, disability, and life coverage
  • 25 paid vacation days alongside market holidays
  • 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:
  • PhD in Statistics, Computer Science, Machine Learning, Mathematics, or a related STEM field, with outstanding academic achievements
  • Expected to graduate by mid-2027 and available to start full-time employment upon graduation
  • 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.