About the Role: We are seeking a highly skilled and motivated Process Automation Engineer with experience in leveraging Machine Learning (ML) and Internet of Things (IoT) technologies to optimize processes within the pharmaceutical or biotechnology industry. The ideal candidate will have a strong background in process engineering, data analytics, and automation, and will be responsible for leading the digital transformation of our manufacturing and operational workflows. Key Responsibilities: Design, develop, and implement automated solutions for manufacturing and quality control processes using ML and IoT. Collaborate with cross-functional teams (Engineering, Quality Assurance, IT, and Manufacturing) to identify opportunities for automation and process improvement. Develop and deploy predictive models to enhance production efficiency, reduce downtime, and ensure product quality. Integrate IoT sensors and smart devices into production environments to enable real-time data monitoring and analytics. Lead projects to optimize end-to-end process workflows and ensure compliance with regulatory standards (e.g., FDA, GxP). Analyze large datasets from manufacturing systems and IoT devices to uncover trends, anomalies, and insights. Maintain thorough documentation of all automation solutions, including risk assessments and validation protocols. Requirements: Bachelor’s or Master’s degree in Engineering, Computer Science, Biotechnology, or a related field. 5+ years of experience in process automation, ideally within the pharmaceutical or biotechnology sector. Strong understanding of ML algorithms, data analytics, and IoT technologies. Experience with tools such as Python, R, TensorFlow, SQL, and cloud-based data platforms. Hands-on experience with industrial IoT platforms and smart manufacturing technologies. Familiarity with regulatory environments (FDA, GxP, GMP). Strong problem-solving skills and the ability to work in a highly regulated, data-driven environment. Preferred Qualifications Experience with SCADA systems, MES, or other industrial control systems. Knowledge of digital twin technology or real-time simulation modeling. Experience with deployment of AI/ML models in production environments. Show more Show less