Machine Learning Engineer (Additive Manufacturing)

Location: Fremont, California, United States; hybrid

Company

hirify.global develops advanced manufacturing systems and software for additive manufacturing.

What you will do

• Develop machine learning models using in-process sensor data to identify anomalies and quality issues during printing.
• Design datasets, preprocessing pipelines, training workflows, model architectures, and evaluation metrics.
• Build reproducible experimentation workflows and document experiments and results.
• Partner with process and software teams to improve the ingestion, cataloging, versioning, and availability of build data.
• Deploy validated models into production code running on printer hardware, considering performance and reliability.
• Provide Python prototypes, specifications, acceptance criteria, and integration support to software engineers.

Requirements

• Bachelor’s degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field; an advanced degree is preferred.
• At least 3 years of professional experience building and evaluating machine learning models.
• Hands-on experience with computer vision or image-based machine learning, including segmentation, classification, or anomaly detection.
• Strong Python skills and experience with modern machine learning frameworks such as PyTorch; strong programming skills in Python or C++.
• Experience designing ML pipelines, working with structured and unstructured datasets, and using version control, code review, and testing.
• STEM or scientific background with experience applying machine learning to substantive technical or engineering problems.

Nice to have

• 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 and model deployment in production or embedded environments.
• Familiarity with cloud storage and data pipelines such as AWS S3 and batch retrieval workflows.
• Experience applying machine learning to robotics, aerospace, materials, instrumentation, scientific computing, or other physical or experimental domains.

Culture & Benefits

• Collaborate closely with process engineers, software engineers, embedded teams, and other ML engineers.
• Work in a regular salaried, full-time position.
• Participate in an environment focused on practical, high-impact machine learning solutions for advanced manufacturing.