Manufacturing Data & Process AI Integration System Engineer, Additive Manufacturing

Hadrian Automation • Torrance, CA

5d • $135,000 - $220,000 • Onsite

About The Position

Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost. Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built. Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we’re building the future of American manufacturing—and looking for exceptional people to help make it happen. If you’re ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you’re exactly who we’re looking for.

Requirements

• Bachelor's degree in Manufacturing Engineering, Computer Science, Data Science, Materials Science, or related field.
• 4+ years in manufacturing data systems, process engineering, or data-driven manufacturing in a production environment.
• Hands-on experience developing and deploying AI/ML models in an engineering or manufacturing context, including model training, validation, and production deployment.
• Proficiency in Python and relevant ML frameworks (scikit-learn, TensorFlow, PyTorch, or equivalent), and SQL fluency for working with manufacturing data at scale.
• Experience building analytical datasets from structured and time-series manufacturing data, including handling of gaps, resampling, and data quality problems.
• Familiarity with structured problem-solving methodologies (8D, 5 Whys, fishbone) and statistical process control.
• Strong analytical skills, with the ability to connect model outputs to physical process understanding and actionable engineering decisions.
• Ability to work on site full time in Torrance, California, with travel up to 15% [CONFIRM].
• Must be a U.S. person for ITAR purposes — a U.S. citizen, lawful permanent resident, protected individual as defined by 8 U.S.C. 1324b(a)(3), or otherwise eligible to obtain the required authorizations from the U.S. Department of State.

Nice To Haves

• Experience applying AI/ML to metal additive manufacturing — build quality prediction, anomaly detection, melt pool monitoring, or process parameter optimization.
• Background with in-situ process monitoring data: layer imaging, thermal sensing, acoustic emissions, or scanner and galvanometer telemetry.
• Experience supporting qualification data packages for aerospace, defense, or regulated manufacturing environments.
• Familiarity with AMS7032, NIAR/NCAMP, or US Navy AM qualification requirements.
• Experience with MLOps practices — model versioning, monitoring, retraining pipelines, and production deployment.
• Experience with closed-loop or feedback control of a manufacturing process using model output.

Responsibilities

• Own the monitoring and analytics layer for the AM fleet — what is computed from raw machine and build data, what is surfaced, and what triggers an alert, at the fidelity traceability and modeling require.
• Own the curated datasets, feature definitions, labeling, and dataset versioning, built on the canonical machine data model and pipelines owned by the Machine Controls & Data Integration Engineer.
• Design, develop, and deploy models trained on Hadrian manufacturing data to predict build quality, detect process anomalies, and identify parameter optimization opportunities.
• Build and maintain the feature engineering and model infrastructure — data quality checks, labeling workflows, model versioning, and model performance tracking in production.
• Develop process monitoring dashboards and AI-driven alerting that give engineering and operations real-time visibility into machine and build health.
• Integrate model outputs back into OPUS and the manufacturing workflow so predictions drive action, and work toward closed-loop parameter adjustment.
• Collaborate with Materials and Process and Application Engineering to validate model outputs against physical process knowledge before they influence production decisions.
• Apply SPC to AM process data, and establish the control limits and drift detection that flag a machine leaving its qualified operating envelope.
• Supply capability, repeatability, and process analysis in support of qualification — machine capability data to the System Qualification Engineer for installation and operational qualification, and performance qualification analysis support to Materials and Process and Application Engineering for customer data packages.
• Lead structured problem-solving on process escapes and build anomalies using 8D, 5 Whys, and fishbone analysis, driving corrective and preventive action to verified closure.

Benefits

• Medical, dental, vision, and life insurance plans for employees
• 401k
• Relocation support may be provided for certain situations, based on business need.
• Flexible vacation policy
• Equity

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level