About the company
Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.
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.
Requirements
- 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 related areas.