2027 Machine Learning Summer Internship

Advanced Space develops software, mission services, and technology solutions for sustainable space exploration. The 2027 Machine Learning Summer Intern will design, develop, test, and apply machine learning models to aerospace engineering challenges, collaborate with aerospace and software engineers, and document and present technical findings.

What you'll 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

What they're looking for:

• 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
• * 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

Benefits:

• 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