Machine Learning Research Engineer

Our client, a leading AI technology firm, is focused on crafting innovative solutions tailored for enterprise and real-world applications. They are currently seeking a ML Research Engineer to enhance their AI Product team based in Singapore.

This position offers a hands-on opportunity for individuals eager to engage in deep work with machine learning and deep learning models, going beyond merely utilizing pre-trained models or APIs.

Your responsibilities will include:

• Designing and testing various neural network architectures, specifically CNNs and/or Transformer-based models
• Training, fine-tuning, and enhancing deep learning models for real-world AI applications
• Conducting structured experiments to assess model performance and reliability
• Utilizing diverse training strategies, architectures, and optimization techniques
• Selecting suitable loss functions and comprehending their effects on model performance
• Assessing model generalization to unseen data and exploring potential constraints
• Analyzing experimental outcomes and pinpointing avenues for enhancing accuracy, robustness, and efficiency
• Handling datasets and data preparation as part of the model development workflow
• Creating prototypes and proof-of-concept solutions to validate novel AI methodologies
• Investigating contemporary AI advancements, including Transformer-based, LLM, and/or Vision-Language Model technologies
• Collaborating with product and engineering teams to transform research findings into practical, production-ready solutions
• This role encompasses the entire ML research and development lifecycle, from selecting architectures and conducting experiments to evaluating and optimizing models.

Qualifications:

• Master's or PhD in Computer Science, AI, Machine Learning, Mathematics, Engineering or a related technical discipline
• Proven experience with neural network architectures, particularly CNNs and/or Transformer-based models
• Demonstrated capability in training, fine-tuning, evaluating, or enhancing deep learning models, as opposed to solely using pre-trained models or AI APIs
• Experience in evaluating model generalization on unseen datasets
• Comprehension of loss functions and the ability to articulate the rationale behind a selected loss function
• Capability to explain and justify the model architecture employed in previous AI/ML projects
• Robust foundation in deep learning principles, model training, and optimization
• Proficient programming skills in Python
• Genuine enthusiasm for AI/ML research and deep learning

Preferred Qualifications:

• Familiarity with PyTorch, TensorFlow, or similar frameworks
• Experience with LLMs, VLMs, or foundational models
• Background in transfer learning, fine-tuning, or knowledge distillation
• Research publications or academic endeavors in AI/ML
• Exposure to fields such as computer vision, NLP, reinforcement learning, edge AI, robotics, speech, or time-series modeling

Dear Candidate,

If you or someone you know is interested in this opportunity, please forward your CV directly to [HIDDEN TEXT] (this method is preferred, as I might miss some applications due to the high volume).

Please be aware that visa sponsorship is not currently available.