Constellation Space
Graduate/PhD Research Intern, Machine Learning
About this role
Constellation is seeking a graduate-level ML research intern to develop forecasting and anomaly detection models for satellite network operations. You'll design experiments, build reproducible workflows, and translate research into prototypes that drive product decisions.
What you'll do
- Design and execute ML experiments for network operations forecasting and risk prediction
- Develop and evaluate time-series, probabilistic, and simulation-informed models
- Improve feature engineering, data quality, and evaluation methodologies
- Build reproducible research workflows for model training, validation, and comparison
- Communicate findings through technical documentation and recommendations
- Own projects end-to-end from scoping through implementation and testing
What they're looking for
- Machine learning (time-series, probabilistic models)
- Python
- C++ or Rust
- Experiment design and rigor
- Data pipeline development
- Scientific computing and ML tooling
- Technical writing and communication
- Reproducible research practices
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Constellation Space
Constellation Space builds ConstellationOS, an autonomous operating system for satellite networks that handles high-volume telemetry and enables real-time routing and operational decisions. The company is hiring Machine Learning Engineers, Flight Software Engineers, and ML research interns to develop core flight systems, deploy ML models for orbital operations, and create forecasting and anomaly detection capabilities.
View all jobs at Constellation SpaceLikely interview questions
- Walk us through a machine learning project you've worked on. How did you approach the problem, and what challenges did you face?
- Describe your experience with deep learning frameworks like PyTorch or TensorFlow. Which do you prefer and why?