True Anomaly
Machine Learning Engineer (II-III), Space Edge Deployment
About this role
True Anomaly seeks a Machine Learning Engineer (II-III) to develop ML and AI capabilities for autonomous spacecraft and space security systems. You'll design classification models, anomaly detection systems, and data pipelines while working alongside experienced engineers in a mission-driven environment focused on space domain awareness.
What you'll do
- Develop, train, and evaluate machine learning models for object classification and anomaly detection tasks
- Build and maintain data ingestion, preprocessing, and feature engineering pipelines
- Design and run experiments to validate models, tracking results and iterating based on findings
- Write clean, documented, and tested Python code within a collaborative engineering team
- Contribute to model evaluation frameworks and support deployment of ML systems
- Learn from senior engineers and grow technical expertise in space-relevant applications
What they're looking for
- Python programming
- Machine learning fundamentals (supervised/unsupervised learning, model evaluation)
- ML frameworks (PyTorch, TensorFlow, or JAX)
- Linear algebra, statistics, and probability
- Git and version control
- Classification, regression, clustering, and anomaly detection techniques
- Deep learning or computer vision
- MLOps concepts (experiment tracking, model versioning)
Benefits
- Comprehensive health, dental, and vision coverage
- HSA/HRA options
- 401(k) retirement plan
- Paid time off and paid holidays
- Parental leave
- Equity compensation
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True Anomaly
True Anomaly develops advanced spacecraft and aerospace defense systems for mission-critical space applications. The company is hiring mechanical, thermal, systems, and test engineers to design, test, integrate, and verify complex space vehicle systems.
- Website
- trueanomaly.com
Likely interview questions
- Walk us through a machine learning project you've built—what was the problem, your approach, and how did you evaluate success?
- How would you approach building an anomaly detection system for satellite imagery or space-based data?