Collaborate with Manufacturing teams to incorporate Design for Manufacturability (DFM) improvements that enhance product quality, yield, and reliability.
Develop proof-of-concept (POC) designs and prototypes to validate redesign approaches and gain technical approval from RF domain experts.
Support PCB layout reviews and contribute to filter, analog, and RF circuit design improvements.
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Good understanding of IT systems and technologies, including SQL, Oracle, Linux, Python, and scripting languages.
Highly motivated and proactive, with the ability to take ownership of applications and projects while serving as a key interface between Process Engineering and Automation teams.
Excellent command of the English language, both written and spoken, is mandatory.
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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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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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Integrate DFM inputs from MFG to improve product yield & quality
Research and propose alternative parts with effective solutions in consideration of avoiding major software & product calibration, hardware topology changes to replace EOL parts in RF products.
Proactive in doing mock-up design as POC (Proof of Concept) to strengthen re-design proposal to get final approval from RF domain leaders.
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Candidates should possess Communication skills to collaborate effectively across engineering, manufacturing, and customer-facing teams, and to create clear technical documentation.
Beneficial qualifications include a bachelor’s or master’s degree in Electrical, Electronics, Mechanical, or related engineering field; experience with automated test systems; familiarity with NI/Emerson tools and platforms; and knowledge of quality and reliability engineering practices.
Additional skills include problem-solving, project management, and a track record of working in high-tech or semiconductor manufacturing environments.
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Conduct and execute RODI and Water Treatment system improvements on reliability hardening, safety performance as well as cost optimization and reduction
Perform facility inspections and report on condition affecting operations
Derive plan and monitor RODI and Water Treatment predictive and preventive maintenance program supervise outsource service contracts
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