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Strong employer, mid-level ML role, metro location, and broad required skillset increase applicant competition.
Core ML/AI skills are transferable but semiconductor and smart-manufacturing integration preferences increase domain specificity.
Explicit 5+ years plus many mandatory technical skills and cloud/Kubernetes/ML requirements raise shortlisting strictness.
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Design, develop, deploy, and support end-to-end AI-powered applications and solutions to enhance manufacturing operations across global fabs and assembly/test sites.
Develop scalable AI web applications, APIs, and automation tools integrating structured and unstructured data, including GenAI technologies and robotics platform integration.
Maintain containerized AI solutions using Docker and Kubernetes/OpenShift; contribute to CI/CD pipelines, model governance, and continuous performance optimization.
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field (or equivalent industry experience).
Minimum 5 years experience building and shipping production web or AI applications end to end.
Proficiency in Python and Angular/TypeScript; experience with Docker, Kubernetes/OpenShift, CI/CD practices, and at least one cloud platform (AWS, Azure, or GCP).
Working knowledge of GenAI technologies including prompt engineering, LLM integration, Responsible AI practices, and machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
Experienced in developing full-stack AI applications in manufacturing or industrial automation environments, preferably semiconductor manufacturing.
Familiar with smart manufacturing workflows, MES, Industrial IoT, equipment automation, and MLOps/model deployment in enterprise contexts.
Demonstrates strong data architecture skills, AI literacy for applying advanced AI tools responsibly, and ability to integrate complex AI/ML models into production-grade systems under CI/CD frameworks.