全职 Data Automation Engineer (AI - Computer Vision) 工作, 薪水, Accion Labs Pulau Pinang 公司招聘中 - Ricebowl

Job Title : Data Automation Engineer (AI & Computer Vision) – Contract

Job Summary: We are looking for a specialized Data Automation Engineer under SIP process engineering department to spearhead advanced defect analysis projects. You will be responsible for developing and deploying real-time automation systems that utilize AI/ML and Computer Vision to identify production defects and manage Quality Discrepancy Notification (QDN) lot containment. This is a critical role aimed at achieving "zero-defect" manufacturing through intelligent, hands-off data orchestration.

Key Responsibilities

1. Intelligent Defect Analysis & Containment

· CV-Driven Inspection: Develop and maintain Computer Vision models for real-time automated defect recognition on the production line.

· QDN Automation: Architect an automated QDN Lot Containment system that triggers immediate holds or re-routing of suspected sub-standard lots based on AI-detected anomalies.

· Real-Time Commonality Analysis: Design systems that perform live commonality analysis across multiple equipment sets and batches to pinpoint root causes of defects as they occur.

2. System Integration & Optimization

· End-to-End Automation: Build seamless data pipelines that connect equipment-level sensors to factory MES (Manufacturing Execution Systems) for instantaneous decision-making.

· MLOps Lifecycle: Manage the deployment, monitoring, and retraining of ML models to ensure high accuracy and low false-positive rates in a live production environment.

· Dashboarding & Reporting: Create real-time visibility tools for engineering teams to monitor lot status and containment efficiency.

Required Skills & Qualifications

· Type: Contract Basis (Renewable based on project milestones).

· Educational Background: Bachelor’s degree in Automation Engineering, Computer Science, Data Science, or a related technical field.

· AI/ML Expertise: Proven experience in building and deploying Machine Learning models for classification and anomaly detection.

· Computer Vision: Strong proficiency in image processing libraries and deep learning frameworks for visual inspection.

· Programming Mastery: High level of competence in Python (for AI/ML) and SQL (for data extraction/analysis).

· Manufacturing Knowledge: Familiarity with QDN processes, lot tracking, and semiconductor/electronics manufacturing flows is highly preferred.

· Soft Skills: Strong analytical problem-solving skills and the ability to work independently in a fast-paced project environment.