ML Summer Intern — Spaceflight AI & Autonomy

Advanced Space; Westminster (MD); On-site; USD 39,000 - 51,000; Full time

Benefits offered by this job

Housing stipend

Mentorship from technical staff

Project work tied to space missions

Job summary

Advanced Space is offering a 2027 Machine Learning Summer Intern position. You will design, develop, test, and apply ML models to support space missions, with mentorship from experienced engineers and researchers.

The role focuses on applying ML to spacecraft autonomy, anomaly detection, NLP, and uncertainty quantification, while collaborating across engineering teams to deliver mission-ready solutions.

Qualifications

• Currently pursuing a degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
• Experience programming in Python and data processing with Pandas/NumPy/Scikit-learn.
• Experience with ML frameworks TensorFlow or PyTorch.
• Understanding ML concepts: supervised/unsupervised learning, classification, regression, clustering, dimensionality reduction.
• Familiarity with Git version control.

Responsibilities

• Develop machine learning solutions for aerospace applications.
• Research, implement, and evaluate state-of-the-art ML algorithms to solve engineering problems.
• Build and test ML models and systems for mission-focused applications.
• Analyze data, preprocess features, and optimize performance of ML solutions.
• Collaborate with aerospace and software engineers to integrate ML solutions.
• Document work and present results through reports and presentations.

Skills

Python

Pandas/NumPy/Scikit-learn

TensorFlow/PyTorch

Git version control

Problem solving

Education

Pursuing degree in Computer Science/Engineering/Mathematics/Statistics

Tools

CUDA C/C++

GPU computing

Jupyter

Job description

Advanced Space is offering a 2027 Machine Learning Summer Intern position. You will design, develop, test, and apply ML models to support space missions, with mentorship from experienced engineers and researchers.

The role focuses on applying ML to spacecraft autonomy, anomaly detection, NLP, and uncertainty quantification, while collaborating across engineering teams to deliver mission-ready solutions.