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Machine Learning Nasa Jobs (NOW HIRING)

$100 - $150/hr

In support of NASA Langley Research Center's Aeronautics Systems Engineering Branch, AMA is seeking highly skilled candidates in the field of Artificial Intelligence / Machine Learning. Specifically ...

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

Job Title MACHINE LEARNING ENGINEER Location Huntsville, AL US (Primary) Category Engineering Job ... NASA, DIA, and FBI. Ignite exists to outpace the threat and deliver results that matter in the ...

You'll collaborate closely with machine learning scientists, software engineers, and robotics ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

What You'll Get To Do Machine Learning modeling * Design, train, and deploy state-of-the-art ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

Senior Machine Learning Engineer

Seattle, WA · On-site

$118K - $163K/yr

What You'll Get To Do Machine Learning modeling * Design, train, and deploy state-of-the-art ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

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Machine Learning Nasa information

What does a machine learning specialist at NASA do?

Machine Learning specialists at NASA use advanced algorithms and data analysis techniques to help solve complex problems in space exploration and research. Their work includes developing models for spacecraft navigation, analyzing satellite imagery, predicting equipment failures, and supporting scientific discoveries through data-driven insights. By leveraging artificial intelligence and machine learning, they help NASA make more accurate predictions, automate processes, and enhance mission safety and efficiency.

What are the key skills and qualifications needed to thrive as a machine learning scientist at NASA?

To thrive as a Machine Learning Scientist at NASA, you need a solid background in computer science, mathematics, and statistics, typically supported by an advanced degree in a related field. Proficiency with programming languages like Python or R, familiarity with machine learning libraries (such as TensorFlow or PyTorch), and experience with large-scale data analysis are essential. Strong problem-solving skills, creativity, and the ability to collaborate across multidisciplinary teams help set top candidates apart. These skills and qualities are crucial for developing innovative AI solutions that support NASA’s scientific missions and research objectives.

What are common challenges faced by machine learning professionals working at NASA, and how can applicants prepare for them?

Machine learning professionals at NASA often work with complex, high-dimensional datasets collected from space missions, satellites, and simulations, which can present unique challenges such as data sparsity, noise, and the need for robust, interpretable models. Collaboration with scientists and engineers from diverse backgrounds is frequent, requiring excellent communication skills to translate technical findings into actionable insights. To prepare, applicants should familiarize themselves with domain-specific data, stay updated on the latest advancements in machine learning, and practice interdisciplinary teamwork to effectively contribute to NASA's innovative projects.

Does NASA use machine learning?

NASA employs machine learning techniques across various projects, including satellite data analysis, spacecraft navigation, and climate modeling. Machine learning helps improve data processing efficiency and supports autonomous systems in space exploration. Job roles in this field often require knowledge of data science, programming, and domain-specific applications.
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Infographic showing various Machine Learning Nasa job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

2027 Machine Learning Summer Internship

Westminster, CO • On-site

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

$28 - $37/hr

Temporary, Internship

Posted 8 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.