Role description
Job Summary
Design and lead the deployment of end-to-end AI systems—from sensor data ingestion (IoT) to edge/cloud model execution—specifically for industrial use cases like predictive maintenance, quality inspection, and supply chain optimization. As an AI/ML Architect for manufacturing focuses on bridging the gap between factory floor operations and advanced data science to drive industrial efficiency
Key Responsibilities
- Infrastructure Design: Build scalable pipelines for High-Frequency Industrial Data (PLC, SCADA, ERP)
- Edge Computing: Deploy models onto shop-floor hardware for real-time latency requirements
- Computer Vision: Implement automated optical inspection (AOI) for defect detection
- Digital Twins: Architect simulation environments to test "what-if" production scenarios
- MLOps: Establish CI/CD for retraining models as manufacturing conditions drift
Technical Skills
- Frameworks: PyTorch, TensorFlow, Scikit-learn
- IIoT Protocols: MQTT, OPC-UA, Modbus
- Cloud & Edge: Azure IoT Edge, AWS IoT Greengrass, NVIDIA Jetson
- Data Engineering: Spark, Kafka, Snowflake, or Time-Series databases (InfluxDB)
- Compliance: Knowledge of ISO standards and manufacturing cybersecurity
Qualifications
- Education: Master’s or PhD in CS, Robotics, or Electrical Engineering
- Experience: 8+ years in software architecture, with 4+ years focused on ML
- Industry Knowledge: Deep understanding of Lean Manufacturing or Six Sigma is a plus
Skills
spark,pytorch,mqtt,iot edge,aws iot,
About UST
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world’s best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients’ organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact—touching billions of lives in the process.
