Lead Research Engineer at Economic… · Singapore

Lead Research Engineer Location: Singapore Polytechnic [What the role is] Most Positive Workplace Collaboration Award – Singapore International Chamber of Commerce (SICC) Awards 2025 Ranked #19 for The Straits Times Singapore’s Best Employers 2024 & 2025 The Centre of Excellence in Maritime Safety (CEMS) is a national R&D centre, a collaborative effort between Singapore Polytechnic and the Singapore Maritime Institute. We focus on developing innovative digital solutions and training systems to enhance maritime safety. Our state-of-the-art research facilities, including South-east Asia's first navigation research simulator, setting us as an innovation champion. You will join CEMS as a Senior AI Engineer/Lead and play a key role in developing applied AI solutions for real-world use cases across training, assessment, operations, research, and digital transformation. The role requires strong hands-on experience in computer vision and/or speech recognition, with the ability to design, develop, evaluate, and deploy AI models. You will work on centre-level AI projects and may also contribute to department- and school-level AI initiatives involving broader AI adoption across R&D, operations, and education. As a senior member of the team, you will also supervise and guide AI engineers, support project planning, and ensure technical delivery across multiple AI workstreams. [What you will be working on] Responsibilities Design, develop, and implement AI models and pipelines for real-world applications in training, assessment, safety, operations, and decision-support. Develop AI solutions involving video analytics, object detection, image classification, visual attention analysis, speech-to-text, audio processing, communication analysis, and related applied AI tasks. Work with data from video, audio, sensors, simulators, operational systems, and other sources to develop AI-enabled analytics and assessment capabilities. Integrate AI models with software platforms, dashboards, simulators, sensor systems, training platforms, or decision-support tools to support practical deployment and operational use. Explore, evaluate, and prototype suitable AI techniques, including deep learning, sequence models, multimodal learning, natural language processing, and large language model applications where relevant. Lead AI components within R&D projects, manage technical milestones, prepare documentation, and ensure timely delivery of project outputs. Supervise and mentor AI engineers or junior team members, review technical approaches, guide model development, and support capability building within the AI team. Work with internal teams, academic staff, industry partners, and external stakeholders to co-develop AI solutions and apply AI capabilities across centre-, department-, and school-level initiatives. Present AI approaches, findings, prototypes, and project outcomes to management, project partners, and industry collaborators in a clear and practical manner. [What we are looking for] Qualifications Tertiary Qualification in Computer Science, Artificial Intelligence, Computer Engineering, Data Science, or a related field. Strong hands-on experience in computer vision and/or speech recognition, including model development, training, evaluation, and deployment. Relevant technical experience may include video analytics, object detection, image classification, pose or behaviour recognition, visual attention analysis, speech-to-text, audio processing, speaker or communication analysis, natural language processing, or multimodal AI involving video, audio, sensor, simulator, or time-series data. Proficiency in Python and experience with AI/ML frameworks and toolkits such as PyTorch, TensorFlow, OpenCV, Hugging Face, or equivalent. Strong understanding of machine learning and deep learning model development, including data preparation, model training, evaluation, optimisation, and performance validation. Experience integrating AI models into software systems, dashboards, simulators, training platforms, or operational applications is preferred. Experience with Large Language Models (LLMs) is an added advantage, particularly in applications beyond standard chatbot or document Q&A systems, such as multimodal AI, speech/video understanding, automated assessment, structured information extraction, model evaluation, fine-tuning, or integration with operational software systems. Experience leading AI workstreams, supervising technical staff, or mentoring junior engineers is preferred. Strong problem-solving ability, project execution skills, communication skills, and ability to work with both technical and non-technical stakeholders.