Kerja Sepenuh Masa, Artificial Intelligence - Machine Learning Engineer di Sandisk WP Kuala Lumpur - Maukerja

We are seeking a Artificial Intelligence & Machine Learning Engineer to architect, deploy, and scale our next-generation manufacturing intelligence systems. In this role, you will own the end-to-end design of robotic process automation (RPA) and advanced machine learning pipelines. You will bridge the gap between complex physical manufacturing processes and digital intelligence, driving operational efficiency and mentoring junior engineers.

Essential Duties and Responsibilities:

• Architect Enterprise Automation: Lead the design and deployment of scalable automation solutions using internal RPA platforms, establishing engineering best practices for structured, fault-tolerant workflow design.
• Process Optimization & Strategy: Analyze complex manufacturing processes, translating them into highly efficient, reliable, and mathematically sound automation flows.
• End-to-End AI/ML Engineering: Own the full lifecycle of computer vision and machine learning pipelines, from data curation to production deployment and model monitoring.
• Advanced Model Development: Design and optimize state-of-the-art deep learning models for classification, object detection, and segmentation (e.g., YOLO, transformers, custom CNNs).
• Data Infrastructure Leadership: Build, scale, and maintain high-throughput image processing and IoT data pipelines handling massive machine and sensor datasets.
• Root Cause & Predictive Analytics: Spearhead advanced data analysis and deep-dive root cause investigations to solve critical manufacturing anomalies and drive continuous process yield improvement.
• Complex System Integration: Formulate integration strategies connecting disparate systems via robust APIs and specialized industrial communication protocols (e.g., SECS/GEM).
• Cross-Functional Ownership: Act as the technical lead across cross-functional teams, overseeing system deployments, debugging high-priority issues, and championing continuous improvement initiatives. 

Required:

• Education: Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, or a highly quantitative field.
• Technical Experience: Minimum of 5–8+ years of professional engineering experience with a proven track record of deploying automation and AI solutions in production.
• Programming Mastery: Expert-level proficiency in Python and C# specifically optimized for industrial automation, computer vision, and real-time data processing.
• Automation Expertise: Advanced expertise in structured workflow design, process flow virtualization, and deploying enterprise-grade models.
• Computer Vision Authority: Deep hands-on experience in full-lifecycle computer vision pipelines:
  • Model training, custom evaluation metrics, and edge/cloud deployment.
  • State-of-the-art (SOTA) Deep Learning models (YOLO variations, SegNet, ResNet).
  • Advanced pixel-level segmentation, multi-class detection, and classification.
  • Conventional computer vision techniques (OpenCV, filtering, morphology, spatial transformations).
• Data Management: Advanced knowledge of SQL (MySQL / MSSQL), including schema design, query optimization, complex stored procedures, and big data handling.
• Analytical Mindset: Demonstrated experience in statistical data analysis and root cause investigation for industrial systems.

Preferred:

• Industrial Domain Expertise: Deep exposure to high-volume manufacturing environments, automated machine vision inspection hardware, or complex sensor telemetry.
• Deep Learning Frameworks: Expert-level familiarity with productionizing models within TensorFlow, PyTorch, or TensorRT ecosystems.

Skills:

• Autonomy & Ownership: Proven ability to operate with minimal supervision, define project roadmaps, and take full accountability for engineering deliverables.
• Influence & Mentorship: Strong communication and interpersonal skills to mentor junior engineers and present technical strategies to non-technical stakeholders.
• Crisis Management: Highly self-driven, analytical, and resilient when troubleshooting critical line-down situations in a high-velocity environment.