Manufacturing Data & Process AI Engineer

Salary: $135,000 - 220,000 per year Requirements:

• Bachelors degree in Manufacturing Engineering, Computer Science, Data Science, Materials Science, or a related field.
• At least 4 years of experience 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 training, validation, and production deployment.
• Proficiency in Python and relevant machine-learning frameworks such as scikit-learn, TensorFlow, or PyTorch, and fluency in SQL for large-scale manufacturing data.
• Experience building analytical datasets from structured and time-series manufacturing data, including addressing data gaps, resampling, and data-quality issues.
• Familiarity with structured problem-solving methods such as 8D, 5 Whys, and fishbone analysis, as well as statistical process control.
• Strong analytical skills and the ability to connect model results with physical process understanding and actionable engineering decisions.
• Ability to work full time on site in Torrance, California, and travel up to 15%.
• Must meet the stated U.S.-person eligibility requirements for ITAR purposes or be eligible to obtain the necessary U.S. Department of State authorizations.
• Preferred: Experience applying AI/ML to metal additive manufacturing, including build-quality prediction, anomaly detection, melt-pool monitoring, or process-parameter optimization.
• Preferred: Familiarity with in-situ process monitoring data, such as layer imaging, thermal sensing, acoustic emissions, or scanner and galvanometer telemetry.
• Preferred: Experience supporting qualification data packages in aerospace, defense, or regulated manufacturing.
• Preferred: Familiarity with AMS7032, NIAR/NCAMP, or U.S. Navy additive-manufacturing qualification requirements.
• Preferred: Experience with MLOps practices, including model versioning, monitoring, retraining pipelines, and production deployment.
• Preferred: Experience with closed-loop or feedback control of a manufacturing process using model outputs.

• Own the additive-manufacturing fleets monitoring and analytics layer, defining how raw machine and build data is analyzed, presented, and used to trigger alerts at the fidelity needed for traceability and modeling.
• Manage curated analytical datasets, feature definitions, labeling, and dataset versioning based on the canonical machine-data model and pipelines maintained by the Machine Controls & Data Integration Engineer.
• Design, develop, and deploy models using manufacturing data to predict build quality, detect process anomalies, and identify opportunities to optimize parameters.
• Build and maintain feature-engineering and model infrastructure, including data-quality checks, labeling workflows, model versioning, and production performance tracking.
• Create process-monitoring dashboards and AI-driven alerts that give engineering and operations teams real-time insight into machine and build health.
• Integrate model outputs into OPUS and manufacturing workflows so predictions inform action, advancing toward closed-loop parameter adjustment.
• Work with Materials and Process and Application Engineering teams to validate model outputs against physical process knowledge before they inform production decisions.
• Apply statistical process control to additive-manufacturing data and establish control limits and drift detection for machines operating outside qualified parameters.
• Provide capability, repeatability, and process analyses for qualification, including machine-capability data for installation and operational qualification and performance-qualification support for customer data packages.
• Lead structured investigations of process escapes and build anomalies using 8D, 5 Whys, and fishbone analysis, and drive corrective and preventive actions through verified closure.

• AI
• Support
• MLOps
• PyTorch
• Python
• Robotics
• SQL
• TensorFlow
• Model Training

More:

We are Hadrian, building autonomous factories to help reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies produce rockets, satellites, aircraft, ships, and other mission-critical systems faster and at lower cost. Following a $1.37 billion Series D at a $7.87 billion valuation, we are expanding our manufacturing footprint and capabilities while scaling our Factory-as-a-Service platform. This role is based full time on site in Torrance, California, with travel of up to 15%, and offers compensation of $135,000–$220,000. Full-time benefits include medical, dental, vision, and life insurance, a 401(k), flexible vacation, equity, and possible relocation support depending on business needs. We use AI-assisted recruiting tools to support our team, but people make all candidate evaluations and hiring decisions; candidates are notified in advance of recorded interviews and may opt out. We consider qualified applicants with criminal histories in accordance with applicable laws and are an equal opportunity employer that provides reasonable accommodations when needed.

last updated 42 week of 2026