True Anomaly
space
MachineLearningEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Machine Learning Engineer at True Anomaly. Skills: machine learning, AI capabilities, model development, pipeline development, object classification, anomaly detection, data ingestion, preprocessing, feature engineering, experiment tracking, model evaluation, model iteration. design and development of machine learning and AI capabilities. development of models and pipelines that enable object classification, anomaly detection, and data-driven decision-making”
What You'll Achieve.
deliver decisive capabilities for space superiority; enable the U. S. and its Allies to secure the space environment and counter threats from the ultimate high ground
Industry & Context.
tackle hard problems
fully onsite role, Candidates must be based in or able to commute to our Denver or Long Beach office daily, 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
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, Foundational understanding of machine learning concepts including supervised learning, unsupervised learning, and model evaluation, mathematical fundamentals in linear algebra, statistics, and probability
Nice to Have
Internship, research, or project experience applying ML to real-world or research datasets, Familiarity with classification, regression, clustering, or anomaly detection techniques, Experience with version control (Git) and basic software engineering practices, Exposure to MLOps concepts such as experiment tracking or model versioning, Coursework or project work in deep learning, computer vision, or time-series analysis
What You'll Do.
design and development of machine learning and AI capabilities
development of models and pipelines that enable object classification
and data-driven decision-making
and evaluation of ML models across a range of mission-relevant tasks
and feature engineering pipelines
and contribute to model evaluation and iteration
and testable Python code
How You'll Work.
Team & Collaboration
Working alongside experienced engineers; contribute to the design and development of machine learning and AI capabilities; support the development of models and pipelines; Learn and grow alongside senior engineers; contributing meaningfully from day one; part of a collaborative engineering 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 contribute to the design and development of machine learning and AI capabilities for True Anomaly. Working alongside experienced engineers, you will support the development of models and pipelines that enable object classification, anomaly detection, and data-driven decision-making. You are curious, driven, and eager to grow — someone who takes ownership of their work and isn't afraid to tackle hard problems. RESPONSIBILITIES Assist in the development, training, and evaluation of ML models across a range of mission-relevant tasks Support data ingestion, preprocessing, and feature engineering pipelines Run experiments, track results, and contribute to model evaluation and iteration Write clean, documented, and testable Python code as part of a collaborative engineering team Learn and grow alongside senior engineers, contributing meaningfully from day one QUALIFICATIONS Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a similar discipline Proficient in Python Foundational understanding of machine learning concepts including supervised learning, unsupervised learning, and model evaluation Exposure to ML frameworks such as PyTorch, TensorFlow, or JAX through coursework, research, or perso
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