Senior AI/ML Engineer

Weare seeking experienced Machine Learning / Generative AI Engineer todesign, develop, and deploy advanced AI/ML and Generative AI (GenAI) solutionsthat optimize manufacturing operations in a high-volume production environment.Thisrole focuses on leveraging machine learning, predictive analytics, andautomation technologies to improve production yield, reduce downtime, andenable smart factory capabilities aligned with Industry 4.0 principles.KeyResponsibilitiesModelDevelopment & DeploymentDesign, build, and deploy machine learning models for predictive maintenance, anomaly detection, and process optimization. Develop GenAI-powered applications, including automated reporting tools, intelligent chatbots, and manufacturing scenario simulations. Translate research-oriented algorithms into scalable, production-ready solutions using MLOps best practices. DataEngineering & IntegrationDevelop robust data pipelines to collect, clean, and transform sensor, MES, and IoT data for model training and inference. Integrate AI models with factory control systems and Manufacturing Execution Systems (MES) to support real-time decision-making. PredictiveAnalytics & Quality ControlApply AI and machine learning techniques to forecast equipment failures, optimize production schedules, and improve product quality. Utilize computer vision and deep learning technologies for automated defect detection and quality assurance. Automation& Continuous ImprovementImplement AI-driven workflows and GenAI-based conversational assistants to reduce manual intervention and improve operational efficiency. Monitor model performance, detect model drift, and automate retraining processes to maintain model accuracy and reliability. Collaboration& ReportingCollaborate closely with engineering and IT teams to align AI and GenAI initiatives with manufacturing objectives. Communicate insights, recommendations, and performance metrics through dashboards and GenAI-generated natural language summaries. Required SkillsTechnicalExpertiseProficiency in programming languages such as Python, R, or Java. Hands-on experience with machine learning frameworks, including TensorFlow, PyTorch, and Scikit-learn. Strong understanding of machine learning algorithms, deep learning architectures, and statistical analysis methods. Familiarity with MLOps tools and platforms such as MLflow, KServe, Docker, and Kubernetes. Experience with CI/CD pipelines and deployment automation. DomainKnowledgeUnderstanding manufacturing processes, MES systems, and industrial automation technologies. Experience in predictive maintenance, anomaly detection, and real-time analytics within manufacturing environments. DataEngineering & Data HandlingExpertise in data preprocessing, feature engineering, and handling large-scale sensors and IoT datasets. Knowledge of SQL and NoSQL databases, as well as cloud platforms used for data storage and model deployment. SoftSkillsStrong analytical thinking and problem-solving capabilities. Effective verbal and written communication skills. Ability to work collaboratively in cross-functional teams and manage multiple priorities in a fast-paced environment.