Graduate/PhD Research Intern, Machine Learning

**About Constellation** Constellation is building software to model, predict, and improve satellite network operations. We combine simulation, data/ML workflows, and product-facing platform systems to support better operational decisions. **Role Overview** We are seeking a research-focused ML intern (MS/PhD level) to help advance our modeling and experimentation capabilities. This role is ideal for someone who enjoys turning research ideas into rigorous experiments and high-quality prototypes that can influence real product and platform direction. **Note:** This role requires access to ITAR-controlled data, so we need candidates to be U.S. persons (citizen, green card holder, or asylee/refugee). **What You’ll Do** * Design and run ML experiments for forecasting and anomaly/risk prediction in network operations * Develop and evaluate models using time-series, probabilistic, and simulation-informed approaches * Improve feature engineering, dataset quality, and evaluation methodology * Build reproducible research workflows for training, validation, and model comparison * Communicate findings through clear technical writeups and recommendations **What We’re Looking For** * Currently enrolled in an MS or PhD program (CS, EE, Aerospace, Applied Math, or related) * Strong low level engineering skills and comfort with scientific/ML tooling (C\+\+, Python, Rust) * Ability to own projects end-to-end: scoping, implementation, testing, and communication * Clear written/verbal communication and strong collaboration habits **Nice to Have** * Experience with APIs, cloud infrastructure, or data-intensive systems * Familiarity with model evaluation, experiment tracking, and reproducibility * Background in networking, geospatial systems, telecom, or space-tech