True Anomaly
space
SeniorMachineLearningEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Machine Learning Engineer at True Anomaly. Skills: machine learning, AI, object classification, anomaly detection, threat assessment. 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”
What You'll Achieve.
deliver decisive capabilities for space superiority; advance technology at the intersection of artificial intelligence, machine learning, and data-driven decision-making; ensure reliability and performance in real-world conditions
Industry & Context.
solve complex problems from first principles
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., Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.
What They're Looking For.
Must Have
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, 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
Nice to Have
Master's or PhD in machine learning, computer science, data science, or a related discipline, background in one of the following core ML disciplines: Anomaly temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job., background in one of the following core ML disciplines: Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.
What You'll Do.
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
and production deployment
and testable code in support of AI/ML capabilities
How You'll Work.
Team & Collaboration
Collaborate with cross-functional teams to translate operational requirements into robust, production-ready ML capabilities; work in a multidisciplinary team
Full Job Description
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 en
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