Machine Learning Engineer

Join our team as a Machine Learning Engineer, where you will develop and deploy machine learning solutions for quality assurance and process monitoring in additive manufacturing. You will work closely with process engineers, software engineers, and fellow ML engineers, using image, time-series, and machine log data from advanced manufacturing systems. Prior experience in additive manufacturing is not required, but a strong background in STEM or scientific disciplines with experience in machine learning is essential.

• Develop and deploy machine learning models using image, time-series, and machine log data to identify anomalies and quality issues during additive manufacturing processes.
• Design and iterate on training and evaluation workflows, including dataset design, preprocessing pipelines, and model architectures, ensuring reproducibility and documentation of experiments.
• Collaborate with cross-functional teams to improve data collection and management processes, and work with software and embedded teams to integrate validated models into production code.
• Strong programming skills in Python or C++
• Experience designing ML pipelines: data loading, preprocessing, training, evaluation, and experiment tracking
• 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)
• Comfort working in a production software environment: version control, code review, testing, and cross-functional collaboration
• Experience organizing and working with structured and unstructured datasets
• 3+ years of experience building and evaluating machine learning models in a professional setting
• Background in a STEM or scientific discipline, with demonstrated use of ML to address substantive technical or engineering problems
• Ability to communicate technical tradeoffs clearly to engineers and non-engineers
• Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field; advanced degree preferred
• Experience with powder bed fusion or other additive manufacturing processes
• Knowledge of manufacturing data workflows, IoT sensor data, or industrial automation systems
• Experience with image-based or time-series machine learning
• Familiarity with model deployment in production or embedded environments
• Familiarity with cloud storage and data pipelines (e.g., AWS S3, batch retrieval workflows)
• Experience in domains such as robotics, aerospace, materials, instrumentation, scientific computing, or other fields where ML is applied to physical or experimental data