Senior Machine Learning Engineer, True Anomaly

• 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
• Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job
• Physical demands—the physical demands of the job, including bending, sitting, lifting and driving

Desirable

• 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
• 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