AI Vision Engineer - Model Engineering & CV Systems

CYNAPSE PTE. LTD.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

cynapse.ai is seeking a Junior to Mid-Level Machine Learning Engineer to join our Model Engineering Team in Singapore. You will work across the full model lifecycle, from dataset prep to training, evaluation, and optimisation, building robust computer vision systems for real-world use.

You’ll collaborate with senior engineers, experiment with data-centric approaches, and push performance through careful analysis and new architectures.

Qualifications

• Bachelor’s degree in Computer Science, AI, ML, Data Science, or related field.
• At least 2 years of hands-on experience training, fine-tuning, and evaluating computer vision models.
• Hands-on experience with PyTorch and/or TensorFlow.
• Proficiency in Python and familiarity with Linux environments and command-line tools.

Responsibilities

• Train, fine-tune, and evaluate computer vision models for classification, detection, segmentation, pose estimation, and action recognition.
• Contribute to model development via architecture enhancements, custom heads, loss functions, and training strategy optimisation.
• Design and execute experiments to evaluate model improvements and performance trade-offs.
• Prototype, benchmark, and assess new architectures and techniques against baselines.
• Investigate edge cases and performance limitations to improve accuracy, robustness, and efficiency.
• Consider practical constraints such as latency, throughput, and hardware-specific optimisation.
• Collaborate with engineering teams to improve dataset quality, model performance, and system reliability.

Skills

PyTorch

TensorFlow

Python

Linux

Education

Bachelor’s degree in Computer Science or related field

Tools

PyTorch

TensorFlow

Job description

cynapse.ai is seeking a Junior to Mid-Level Machine Learning Engineer to join our Model Engineering Team in Singapore. You will work across the full model lifecycle, from dataset prep to training, evaluation, and optimisation, building robust computer vision systems for real-world use.

You’ll collaborate with senior engineers, experiment with data-centric approaches, and push performance through careful analysis and new architectures.