Develop and present test plans when problems arise, coordinate testing and data acquisition
Candidates must possess a recognized Degree in Engineering, Electrical/ Electronics/ Communication Engineering or equivalent with minimum 1 year working experience.
Possess analytical/ problem solving skills, data acquisition skills, and ability to use statistical tools and techniques such as CP & CPK study.
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3) Setup various test stations, workstations, machines, tools and equipment in production lines for supporting new product introduction, capacity increase, productivity improvement and other business needs.
Evaluate, fine-tune, and improve AI systems through structured testing, quality measurement, safety guardrails, and hallucination reduction techniques.
Design and implementation of machine learning models in different domains (e.g. SCM, Manufacturing, Product Management and Corporate Functions) following the CRISP- DM process.
Train, fine-tune, and optimize deep learning models for various applications.
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Perform product conversions on test equipment to support various production requirements.
Monitor key process input variables (KPIVs) using tools such as the KPOV database, OEE tracking, Maintenance Logs, and the Digital Preventive Maintenance system.
Drive and support equipment upgrade and continuous improvement projects to enhance performance and efficiency.
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Developers will be involved in reviewing current state design and working with the technical lead to define future state design, document, review, develop, test, and implement code features. Our group creates and maintains decision support tools in support of Intel's Supply Chain. Working as a member in an Agile Scrum, developers are involved in all aspects of the software development lifecycle.
7+ years of hands-on experience in Data Science, Machine Learning, LLMs and AI.
Deep understanding of Retrieval-Augmented Generation (RAG) architectures, including embeddings, vector databases, semantic search, and retrieval optimization techniques.
Knowledge of Knowledge Graphs, semantic data models, ontologies, graph databases (e.g., Neo4j), and their application in enterprise AI solutions.
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Conduct detailed investigations for quality incidents related to test equipment, perform root cause analysis, and implement effective corrective and preventive actions.
Perform product conversions, equipment setup, calibration, and optimization to support various production and engineering requirements.
Monitor and analyze KPIVs using tools such as KPOV database, OEE tracking, Maintenance Logs, and Digital Preventive Maintenance systems to identify trends and drive equipment improvement actions.
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