Machine Learning Research Engineer

Our client is an AI technology company developing advanced solutions for enterprise and real-world applications. They are looking for a ML Research Engineer to join their AI Product team in Singapore.This is a hands-on research and engineering opportunity for someone who wants to work deeply with machine learning and deep learning models, rather than simply consuming pre-trained models or APIs.You will be involved in:Designing and experimenting with neural network architectures, particularly CNNs and/or Transformer-based modelsTraining, fine-tuning and improving deep learning models for practical AI applicationsConducting structured experiments to evaluate model performance and reliabilityWorking with different training strategies, architectures and optimisation approachesSelecting appropriate loss functions and understanding their impact on model performanceEvaluating how models generalise to unseen data and investigating potential limitationsAnalysing experimental results and identifying opportunities to improve accuracy, robustness and efficiencyWorking with datasets and data preparation as part of the model development processDeveloping prototypes and proof-of-concept solutions to validate new AI approachesExploring modern AI developments, including Transformer-based, LLM and/or Vision-Language Model technologiesCollaborating with product and engineering teams to translate research ideas into practical, production-oriented solutionsThe role provides exposure to the full ML research and development lifecycle, from architecture selection and experimentation through to model evaluation and optimisation.Requirements:Master's or PhD in Computer Science, AI, Machine Learning, Mathematics, Engineering or a related technical fieldHands-on experience with neural network architectures, particularly CNNs and/or Transformer-based modelsDemonstrated experience training, fine-tuning, evaluating or improving deep learning models, rather than only consuming pre-trained models or AI APIsExperience evaluating model generalisation on unseen dataUnderstanding of loss functions and the ability to explain why a particular loss function was selectedAbility to explain and justify the model architecture used in previous AI/ML projectsStrong foundation in deep learning concepts, model training and optimisationStrong Python/programming skillsGenuine interest in AI/ML research and deep learningNice to Have:Experience with PyTorch, TensorFlow or similar frameworksExperience with LLMs, VLMs or foundation modelsExperience with transfer learning, fine-tuning or knowledge distillationResearch publications or academic projects in AI/MLExposure to areas such as computer vision, NLP, reinforcement learning, edge AI, robotics, speech or time-series modellingDear Applicant,If you or someone you know is interested, please send the CV directly to [email protected] (most preferred, as I may overlook some CVs due to the high volume).Please note that visa sponsorship is not available at this time.