Manufacturing System Integration Engineer

Samsung•Taylor, TX

5d•Onsite

About The Position

Samsung Austin Semiconductor is seeking a Manufacturing System Integration Engineer to support its semiconductor facilities in Taylor and Austin, Texas. The role connects proprietary production systems with physical manufacturing execution and focuses on troubleshooting factory bottlenecks, optimizing throughput, and using modern software tools and AI to improve employee productivity and operational efficiency. The engineer works with Manufacturing, Systems, Equipment, and Process Engineering teams to implement data-driven improvements in a high-volume production environment. The primary base is Taylor, Texas, with dual-site support for Austin and Taylor. The schedule is a day shift on a compressed work week, with 12-hour shifts three or four days per week. All positions at Samsung Austin Semiconductor are full-time and on-site. The position requires a bachelor's degree in a relevant engineering, data science, or related field and 2 to 5 years of experience in semiconductor manufacturing or a related field. The base salary range is $76,000 to $120,000. Total compensation includes a benefits package and may include participation in company incentive compensation programs. Eligible full-time employees may receive MBO bonuses based on company, division, and individual performance. Employment may be contingent on meeting U.S. Person requirements or the employer obtaining any necessary export license.

Requirements

Bachelor's degree in Industrial Engineering, Electrical Engineering, Mechanical Engineering, Data Science, or a related field.
2 to 5 years of experience in semiconductor manufacturing or a related field.
Deep understanding of manufacturing metrics, including OEE, Utilization, Cycle Time, Throughput, Yield, DPML, SPC, and APC.
Practical application of Lean Manufacturing, Six Sigma, Root Cause Analysis (RCA), and FMEA.
Proficiency with IDEs such as VS Code and Jupyter Lab.
Proficiency with data visualization tools such as Spotfire, Tableau, and/or Power BI for operational dashboards and executive reports.
Strong experience in data mining and statistical analysis, and ability to translate raw system logs into actionable manufacturing insights.
Ability to manipulate large datasets and identify production-line trends, patterns, and anomalies.
Proficiency in Python, with strong fundamentals in Git and structured code.
Experience with API integration, prompt engineering, and building agents that parse structured JSON outputs to facilitate complex functions.
Ability to work on-site in Taylor and Austin, Texas, with a day-shift compressed schedule of 12-hour shifts three or four days per week.

Responsibilities

Resolve system-related issues and eliminate factory bottlenecks using technical expertise.
Analyze production workflows to improve tool throughput and overall system performance.
Collect and interpret data from sensors and automated systems, identify trends, and provide actionable insights.
Audit and map operational workflows to identify redundancies and opportunities for AI and automation.
Analyze daily internal workflows and identify candidates for automation.
Design and deploy tools that reduce manual data entry and streamline document routing.
Design and deploy production-grade AI agents and copilots that help engineers and technicians complete multi-step operational tasks.
Use LLM APIs and proprietary data with retrieval-augmented generation (RAG) to support data processing and task orchestration.
Integrate AI agents into existing software systems using APIs and function calling so tools can trigger actions in manufacturing systems.
Create and maintain automation reports, standard operating procedures, and documentation for system enhancement requests.