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Machine Learning Internship Microsoft Jobs in Colorado

Machine Learning Engineer

Aurora, CO · On-site

$125 - $150/hr

Experience with operationalizing software in the cloud such as AWS, Microsoft Azure, or Google * Experience with Kubernetes * Experience with data science or machine learning * Knowledge of python ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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Machine Learning Internship Microsoft information

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 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 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 cities in Colorado are hiring for Machine Learning Internship Microsoft jobs?

Cities in Colorado with the most Machine Learning Internship Microsoft job openings:

2027 Machine Learning Summer Internship

Westminster, CO

Advanced Space
Guided Missile and Space Vehicle Manufacturing • 11 - 50 employees

$28 - $37/hr

Temporary, Internship

Posted 15 days ago


Job description

Advanced Space | 2027 Summer Internship | Onsite 

We're going to the Moon. Think you've got what it takes? 

About the Role 

At Advanced Space, we're enabling humanity's return to the Moon and building the technologies that will take us to Mars and beyond. We're looking for a 2027 Machine Learning Summer Intern to join our team and help push the state of the art in aerospace applications.

As a Machine Learning Intern, you'll work alongside experienced technical staff who will provide mentorship and guidance throughout your internship. You'll gain hands-on experience designing, developing, testing, and applying machine learning models to solve complex engineering challenges supporting the future of space exploration.

This internship is ideal for students passionate about artificial intelligence, machine learning, aerospace applications, and applied research. You'll have the opportunity to work on meaningful projects while collaborating with engineers and researchers developing innovative solutions for real space missions.

About Advanced Space 

Advanced Space exists to enable the sustainable exploration, development, and settlement of space through innovative software, mission services, and technology solutions. As the owner and operator of NASA's CAPSTONE mission and the Prime Contractor for AFRL's Oracle mission, we're helping shape the future of cislunar exploration while supporting commercial, civil, and national security customers. 

Our team combines deep technical expertise with an entrepreneurial mindset. We move quickly, collaborate across disciplines, and empower every engineer to make meaningful contributions. If you're passionate about solving challenging problems and seeing your work fly in space, you'll fit right in. 

What You'll Actually Do 

Develop machine learning solutions for aerospace applications.

Research, implement, and evaluate state-of-the-art machine learning algorithms and techniques to solve challenging engineering problems.

Build and test ML models.

Design, develop, and improve machine learning models and systems supporting applications such as:

  • Spacecraft autonomy
  • Anomaly detection
  • Natural language processing
  • Uncertainty quantification
  • Multimodal signal detection

Analyze data and optimize performance.

Perform data preprocessing, feature engineering, model evaluation, and optimization to improve the performance, scalability, and reliability of ML solutions.

Collaborate with engineering teams.

Work alongside aerospace and software engineers to integrate machine learning solutions into mission-focused applications.

Share your research and findings.

Document technical work and present project results through reports, presentations, and discussions with the technical team.

Who Thrives Here 

  • You are currently pursuing a degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
  • You have experience programming in Python and working with data processing libraries such as Pandas, NumPy, or Scikit-learn.
  • You have experience with machine learning frameworks such as TensorFlow or PyTorch.
  • You understand foundational machine learning concepts, including supervised and unsupervised learning, classification, regression, clustering, and dimensionality reduction.
  • You are familiar with software development best practices, including Git version control.
  • You enjoy solving complex technical problems and conducting applied research.
  • You communicate technical concepts clearly and collaborate effectively with teammates.

Bonus Points if You Have Experience With

  • CUDA C/C++ or GPU computing
  • High-performance or scientific computing
  • Natural language processing
  • Computer vision
  • Aerospace engineering concepts such as nonlinear estimation, optimization, or control theory
  • Machine learning applied to engineering or scientific problems

Success is Measured By 

  • Developing and evaluating machine learning solutions for real aerospace challenges.
  • Applying ML techniques to meaningful mission-focused projects.
  • Collaborating effectively with engineers and technical staff.
  • Communicating research findings clearly through documentation and presentations.
  • Building technical skills through mentorship and hands-on experience.

Why Join Advanced Space 

  • Gain hands-on experience applying machine learning to real space missions.
  • Work alongside engineers and researchers solving complex aerospace challenges.
  • Contribute to innovative projects supporting missions to the Moon and beyond.
  • Receive mentorship and guidance from experienced technical staff.
  • Be part of a growing company where your contributions directly support mission success.

Compensation & Benefits 

  • Competitive internship compensation: $28-$37/hour
  • Housing stipend
  • Mentorship and guidance from technical staff
  • Opportunities to contribute to research projects directly tied to active space missions
  • Collaborative work environment at our Westminster, Colorado headquarters

Advanced Space is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive workplace for all employees. Employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other protected characteristic under applicable law.Â