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Strong Tier-1 brand, mid-level/staff AI role, and broad full-stack MLOps requirements increase applicant competition.
Core ML, cloud, and MLOps skills transfer across industries, but manufacturing/MES integration adds domain specificity.
Explicit 5+ years plus many mandatory skills (Python, ML, cloud, Kubernetes, Angular, MLOps) raises strictness.
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Design, develop, deploy, and support end-to-end AI-powered applications and automation tools to improve global manufacturing operations.
Develop responsive front-end applications using React, Angular, or Streamlit and backend Python/FastAPI services integrating AI and ML models, including GenAI capabilities, robotic and MES systems.
Build, train, and deploy predictive machine learning models; contribute to CI/CD pipelines, model monitoring, and apply Responsible AI practices in production environments.
Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related field, or equivalent experience.
5+ years of experience building and shipping production web or AI applications end to end.
Strong programming skills in Python and modern Angular/TypeScript, experience with Docker, Kubernetes/OpenShift, and CI/CD practices.
Hands-on experience with at least one cloud platform (AWS, Azure, or GCP); knowledge of GenAI technologies and machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
Experienced in developing scalable AI/ML solutions for industrial or manufacturing environments, ideally semiconductor or smart manufacturing.
Proficient in integrating advanced AI capabilities such as LLMs, agentic AI, and robotics with operational systems like MES and Industrial IoT.
Skilled at implementing end-to-end ML pipelines, continuous delivery, and applying Responsible AI governance in production settings.