Machine Learning Engineer (Space Agentic AI)

Join True Anomaly, a pioneering company in space security. As a Machine Learning Engineer, you will contribute to the design and development of AI capabilities for space domain awareness. You will work alongside experienced engineers, support the development of models and pipelines, and assist in data ingestion, preprocessing, and feature engineering. You will also run experiments, track results, and contribute to model evaluation and iteration. This is a unique opportunity to make a meaningful impact in the field of space security while enjoying a comprehensive benefits package, including 100% employer-sponsored healthcare, generous time off, equity options, and 401k options.

• Contribuer à la conception et au développement de capacités d'apprentissage automatique et d'IA pour True Anomaly.
• Assister au développement, à l'entraînement et à l'évaluation de modèles d'apprentissage automatique pour des tâches pertinentes.
• Écrire du code Python propre, documenté et testable dans le cadre d'une équipe d'ingénierie collaborative.

• Proficiency in Python
• Exposure to ML frameworks such as PyTorch, TensorFlow, or JAX through coursework, research, or personal projects
• Eagerness to learn, take feedback, and grow in a fast-paced, mission-driven environment
• Foundational understanding of machine learning concepts including supervised learning, unsupervised learning, and model evaluation
• Passion for spaceflight and advancing capabilities related to space domain awareness and space security
• Strong mathematical fundamentals in linear algebra, statistics, and probability
• Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a similar discipline, plus 2-4 years of experience; or a Master's degree in one of these fields with no experience required
• To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State
• Internship, research, or project experience applying ML to real-world or research datasets
• Familiarity with classification, regression, clustering, or anomaly detection techniques
• Exposure to MLOps concepts such as experiment tracking or model versioning
• Experience with version control (Git) and basic software engineering practices
• Coursework or project work in deep learning, computer vision, or time-series analysis