01Overview
How You Will Make An Impact .Develop Industrial AI Models: Design, build, and deploy AI/ML models for predictive maintenance, asset performance monitoring, and downtime reduction.Optimize Industrial Processes: Use AI to reduce variability, optimize production schedules, and improve quality control in manufacturing and process industries.Integrate AI with OT Systems: Work with SCADA, PI systems, IoT, MES, and EHS to extract, process, and analyze real-time industrial data.Enhance AI-Driven Automation: Develop AI algorithms that support autonomous operations, fault detection, and prescriptive analytics.Implement Edge AI Solutions: Deploy AI models on edge devices for real-time decision-making at industrial sites.Ensure Scalable AI Deployments: Work with cloud AI platforms (AWS, Azure, GCP) to build scalable AI-driven industrial applications.Collaborate with Cross-Functional Teams: Partner with process engineers, automation teams, and data scientists to deliver AI solutions aligned with business goals.Drive AI Innovation: Stay ahead of emerging trends in generative AI, reinforcement learning, and industrial digital twins to drive continuous improvements.What You Bring to The Team5+ years of experience in industrial AI, machine learning, or data science applied to manufacturing, energy, or process industries.Expertise in time-series analysis, predictive maintenance, anomaly detection, and optimization algorithms .Strong experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn) and big data technologies (Spark, Kafka).Knowledge of industrial protocols (MQTT, OPC UA, Modbus) for AI-driven automation.Experience in cloud AI platforms (AWS Sagemaker, Azure ML, Google Vertex AI) and Edge AI solutions .Familiarity with digital twins, industrial IoT, and APM (Asset Performance Management) systems .Strong problem-solving skills, with the ability to work in fast-paced industrial environments. .
