Machine Learning Engineer (II-III), Space Edge Deployment

Space is a warfighting domain. True Anomaly seeks those with the talent and ambition to build the technology that secures it.

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.

• 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.

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.

• 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

• 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.

• Proficiency 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 personal projects

• Strong mathematical fundamentals in linear algebra, statistics, and probability

• Eagerness to learn, take feedback, and grow in a fast-paced, mission-driven environment

• Passion for spaceflight and advancing capabilities related to space domain awareness and space security

PREFERRED SKILLS AND EXPERIENCE

• 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

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