About the role
Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it. OUR MISSION True Anomaly delivers decisive capabilities for space superiority. We build autonomous spacecraft, advanced payloads, mission software, and space-based interceptors — enabling the U.S. and its Allies to secure the space environment and counter threats from the ultimate high ground. OUR VALUES Be the offset. We create asymmetric advantages with creativity and ingenuity. What would it take? We challenge assumptions to deliver ambitious results. It’s the people. Our team is our competitive advantage and we are better together. YOUR MISSION As a member of the Applied Algorithms and Autonomy team, you will design, build, and deploy core machine learning and AI capabilities for True Anomaly. You will work with a talented cross-functional team to advance technology at the intersection of artificial intelligence, machine learning, and data-driven decision-making. This will involve hands-on development across areas including object classification and discrimination, anomaly detection, and threat assessment. You are a first-principles engineer who takes ownership of the systems you build and delivers results.
RESPONSIBILITIES Design, implement, and test ML/AI models that support threat assessment, object discrimination, and decision-making in operationally relevant environments Own the full ML development lifecycle — from data ingestion and feature engineering through model training, evaluation, and production deployment Collaborate with cross-functional teams to translate operational
requirements into robust, production-ready ML capabilities Establish and maintain rigorous model evaluation practices to ensure reliability and performance in real-world conditions Write clean, well-documented, and testable code in support of AI/ML capabilities
QUALIFICATIONS Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a similar discipline Proficient in Python Solid understanding of statistics, probability, and optimization Experience with ML frameworks such as PyTorch, TensorFlow, or JAX 4+ years of experience designing, training, and deploying ML models in real-world systems Demonstrated ability to work in a multidisciplinary team and solve complex problems from first principles Passion for spaceflight and advancing capabilities related to space domain awareness and space security PREFERRED SKILLS AND EXPERIENCE Master's or PhD in machine learning, computer science, data science, or a related discipline Strong background in one of the following core ML disciplines: Anomaly & outlier detection: statistical, density-based, and deep learning approaches Object discrimination: multi-class and fine-grained classification, metric learning, few-shot learning, evidential reasoning and Dempster-Shafer Theory (DST) for belief combination and conflict resolution under uncertain or incomplete sensor data Unsupervised learning: clustering, dimensionality reduction, generative modeling Sequential and temporal modeling: time-series analysis and sequential modeling Experience deploying models to edge or resource-constrained environments with real-time processing
