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 models

Training, fine-tuning and improving deep learning models for practical AI applications

Conducting structured experiments to evaluate model performance and reliability

Working with different training strategies, architectures and optimisation approaches

Selecting appropriate loss functions and understanding their impact on model performance

Evaluating how models generalise to unseen data and investigating potential limitations

Analysing experimental results and identifying opportunities to improve accuracy, robustness and efficiency

Working with datasets and data preparation as part of the model development process

Developing prototypes and proof-of-concept solutions to validate new AI approaches

Exploring modern AI developments, including Transformer-based, LLM and/or Vision-Language Model technologies

Collaborating with product and engineering teams to translate research ideas into practical, production-oriented solutions

The 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 field

Hands-on experience with neural network architectures, particularly CNNs and/or Transformer-based models

Demonstrated experience training, fine-tuning, evaluating or improving deep learning models, rather than only consuming pre-trained models or AI APIs

Experience evaluating model generalisation on unseen data

Understanding of loss functions and the ability to explain why a particular loss function was selected

Ability to explain and justify the model architecture used in previous AI/ML projects

Strong foundation in deep learning concepts, model training and optimisation

Strong Python/programming skills

Genuine interest in AI/ML research and deep learning

Nice to Have:

Experience with PyTorch, TensorFlow or similar frameworks

Experience with LLMs, VLMs or foundation models

Experience with transfer learning, fine-tuning or knowledge distillation

Research publications or academic projects in AI/ML

Exposure to areas such as computer vision, NLP, reinforcement learning, edge AI, robotics, speech or time-series modelling

Dear Applicant,

If you or someone you know is interested, please send the CV directly to [HIDDEN TEXT] (most preferred, as I may overlook some CVs due to the high volume).

Please note that visa sponsorship is not available at this time.