Computer Vision Model Engineer for Video Intelligence

CYNAPSE PTE. LTD.; Singapore; On-site; SGD 60,000 - 120,000; 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 CV model lifecycle, from data prep and architecture to training, evaluation, and optimisation, building robust vision systems for real‑world applications.

You will collaborate with experienced engineers, experiment with new architectures, and focus on latency, accuracy, and efficiency while staying aligned with our product goals in enterprise video

Qualifications

• Bachelor's degree in CS/AI/ML/Data Science or related field.
• 2+ years hands-on experience training, fine-tuning, and evaluating computer vision models.
• Proficiency with PyTorch and/or TensorFlow; strong Python skills and Linux familiarity.

Responsibilities

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

Skills

PyTorch

TensorFlow

Python

Linux CLI

Education

Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field

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 CV model lifecycle, from data prep and architecture to training, evaluation, and optimisation, building robust vision systems for real‑world applications.

You will collaborate with experienced engineers, experiment with new architectures, and focus on latency, accuracy, and efficiency while staying aligned with our product goals in enterprise video