Computer Vision ML Engineer (Junior–Mid)

Cynapse Pte Ltdcynapse.ai; Singapore; On-site; SGD 60,000 - 120,000; Full time

Job summary

Cynapse Pte Ltd in Singapore is seeking a Junior to Mid-Level Machine Learning Engineer to join the Model Engineering Team. You will work across the full model lifecycle, from data prep to training and optimisation, building robust computer vision systems for real-world applications.

You will collaborate with experienced engineers, experiment with data-centric approaches, and aim to improve model performance while considering latency, throughput, and hardware constraints.

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 CV models.
• Experience with PyTorch and/or TensorFlow.
• Proficiency in Python and Linux environments with CLI.

Responsibilities

• Train, fine-tune, and evaluate CV models for classification, detection, segmentation, pose estimation, and action recognition.
• Improve model architectures and training strategies with custom heads and loss functions.
• Design experiments to evaluate performance trade-offs and improvements.
• Prototype and benchmark new architectures against baselines.
• Investigate edge cases, enhance accuracy, robustness, and efficiency.
• Consider latency, throughput, and hardware-specific optimisation.
• Collaborate with teams to improve data quality, model performance, and system reliability.

Skills

Python

PyTorch/TensorFlow

Linux

Command-line tools

2+ years CV model experience

Multimodal models

Open-vocabulary models

Model optimisation techniques

MLOps practices

Education

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

Job description

Cynapse Pte Ltd in Singapore is seeking a Junior to Mid-Level Machine Learning Engineer to join the Model Engineering Team. You will work across the full model lifecycle, from data prep to training and optimisation, building robust computer vision systems for real-world applications.

You will collaborate with experienced engineers, experiment with data-centric approaches, and aim to improve model performance while considering latency, throughput, and hardware constraints.