Cloud Computing

1. Conducts research to advance the field of artificial intelligence, develops new algorithms, and publishes findings. 2. Designs builds, and deploys machine learning systems, optimises performance, and integrates models into production environments. 3. Analyses complex data sets, develops predictive models using machine learning techniques, and communicates insights to stakeholders. 4. Develop algorithms and models to understand and generate human language, and apply NLP techniques to real-world problems. 5. Designs and implements computer vision algorithms and systems for tasks like image classification, object detection, and video analysis. 6. Investigate the ethical implications of AI technologies, develop frameworks for responsible AI deployment, and advocate for ethical guidelines. 7. Defines AI product strategy, collaborates with cross-functional teams to develop AI-powered products, and ensures alignment with business goals. 8. Designs scalable and efficient AI systems, selects appropriate hardware and software components, and oversees system integration and deployment. 9. Identifies vulnerabilities in AI systems, develops security measures to protect against attacks, and ensures compliance with security regulations. 10. Advises organisations on AI strategy, identifies opportunities for AI adoption, and provides expertise in implementing AI solutions.

1. Develop deep learning/ machine learning algorithms to optimize the production efficiency, quality and people productivity of manufacturing processes, not limited to defect/parts inspection, predictive maintenance, anomaly detection, timeseries forecasting, customized Large Language Model (LLM) / Visual Language Model (VLM), etc 2. Use data to create models, perform statistical analysis, and train and retrain systems to optimise performance

1. Curate, annotate, and refine datasets to train the bot on various intents, entities, and dialogues. 2. Work with natural language processing (NLP) models, refine algorithms, and adjust training parameters to enhance the bot’s performance. 3. Craft conversation flows, responses, and scenarios that are natural, engaging, and aligned with user expectations. 4. Continuously monitor the bot's performance, identify areas for improvement, and implement updates to improve accuracy and user experience. 5. Analyse user interactions and feedback to fine-tune the bot's responses and functionality. 6. Work closely with developers, UX designers, and other stakeholders to integrate the bot into various platforms and ensure it meets business objectives.

1. analyse large datasets using statistical methods and machine learning techniques to extract actionable insights. 2. develop predictive models and algorithms to forecast trends, behavior patterns, and business outcomes. 3. create visualisations and reports to communicate findings and recommendations to stakeholders. 4. implement machine learning models and algorithms for tasks such as image recognition, natural language processing, or recommendation systems. 5. collaborate with cross-functional teams to identify opportunities for data-driven solutions and business improvements. 6. clean and preprocess data to prepare it for analysis and modeling. conduct exploratory data analysis to understand patterns, trends, and anomalies in data. 7. evaluate and select appropriate machine learning models and techniques for specific problems. 8. deploy and maintain machine learning models in production environments. 9. stay updated on advancements in machine learning, artificial intelligence, and data science methodologies.

1) Manages and reviews Health, Safety, and Environmental (HSE) policies, standards, procedures, and the Workplace Safety and Health Management System in line with regulatory requirements and business needs 2) Oversees the implementation of safety practices and procedures, ensuring compliance with relevant health and safety standards, and leads initiatives to promote these practices within the organization. 3) Manages HSE resources, including manpower, internal assets, and external vendors, and develops safety practices, procedures, and guidelines according to health and safety standards. 4) Aligns the organization's WSH policy with business and operational concerns, collaborates with colleagues for effective enforcement of WSH parameters, and stays updated on legislative requirements and industry best practices. 5) Communicates with and manages teams, internal and external stakeholders, and conducts site visits as necessary to maintain and enhance WSH performance. 6) Leads the HSE department, making independent business decisions, and possesses the necessary qualifications

1. Identifies and assesses workplace and work process risks, advising on and recommending measures to eliminate, minimize, or control these risks. 2. Implements measures to prevent or reduce health and environmental risks while improving process quality. 3. Supervises a quality HSE team and collaborates with internal and external stakeholders to achieve organisations' objectives related to workplace safety. 4. Applies analytical and resourceful problem-solving skills, demonstrating strong teamwork and collaboration.