MachineLearningEngineer

## Responsibilities Develop ML models using in-process sensor data to identify anomalies and quality issues during printing. Build and iterate on training and evaluation workflows; document experiments and results for reproducibility. Own ML experimentation end to end: Design datasets, preprocessing pipelines, and training workflows; iterate on model architectures and metrics; document experiments and results for reproducibility. Help define data collection and management: Partner with process and software teams to improve how build data is ingested, cataloged, versioned, and made available for training and evaluation. Deploy models into production: Work with print software and embedded teams to integrate validated models into production code running on printer hardware, including performance and reliability considerations. Collaborate with supporting software engineers: Hand off validated Python prototypes for production hardening, provide clear specifications and acceptance criteria, and support integration and regression testing. ## Requirements Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field; advanced degree preferred. 3+ years of experience building and evaluating machine learning models in a professional setting. Hands-on experience with computer vision or image-based ML (e.g., segmentation, classification, or anomaly detection). Strong Python skills and experience with modern ML frameworks (e.g., PyTorch). Experience designing ML pipelines: data loading, preprocessing, training, evaluation, and experiment tracking. Comfort working in a production software environment: version control, code review, testing, and cross-functional collaboration. Ability to communicate technical tradeoffs clearly to engineers and non-engineers. Strong programming skills in Python or C++. Experience organizing and working with structured and unstructured datasets. Background in a STEM or scientific discipline, with demonstrated