ML Engineer (Computer Vision)

EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 80,000 - 140,000; Full time

Job summary

EVOLUTION RECRUITMENT SOLUTIONS PTE. LTD. in Singapore is seeking a Machine Learning Engineer focused on computer vision to advance classification, detection, segmentation, pose estimation, and action recognition models.

The role emphasizes fine-tuning existing models with opportunities to develop new ones and automate training workflows. You will collaborate with data scientists and software engineers to analyze model performance, compare architectures, and implement robust MLOps pipelines

Qualifications

• Degree in Computer Science, AI, Data Science or related field.
• At least two years of hands-on computer vision experience.
• Strong expertise in object detection, segmentation, pose estimation and action recognition.
• Proficiency in Python and PyTorch and/or TensorFlow.
• Ability to explain model selection, training decisions and evaluation results.
• Familiarity with Linux, Git and reproducible experimentation.

Responsibilities

• Train, fine-tune and evaluate models to improve accuracy and efficiency.
• Compare model architectures and explain their strengths, limitations and trade-offs.
• Analyse model performance, investigate failure cases and test improvements.
• Develop MLOps workflows and write or modify Python scripts to automate model training.

Skills

Computer vision

Model evaluation

Experimentation

Education

Bachelor's degree in Computer Science/AI/Data Science

Tools

Python

PyTorch

TensorFlow

Linux

Git

MLOps

Job description

Machine Learning Engineer - Computer Vision

Role Overview

Develop and improve computer vision models across classification, object detection, segmentation, pose estimation and action recognition. The role focuses primarily on fine-tuning existing models, with opportunities to develop new models and automate training workflows.

Responsibilities

• Train, fine-tune and evaluate models to improve accuracy, robustness and efficiency.
• Compare model architectures and explain their strengths, limitations and trade-offs.
• Analyse model performance, investigate failure cases and test improvements.
• Develop MLOps workflows and write or modify Python scripts to automate model training.

Requirements

• Degree in Computer Science, AI, Data Science or a related field.
• At least two years of hands-on computer vision experience, including academic projects, internships or professional work.
• Strong expertise in object detection, segmentation, pose estimation and action recognition
• Proficiency in Python and PyTorch and/or TensorFlow.
• Ability to explain model selection, training decisions and evaluation results.
• Familiarity with Linux, Git and reproducible experimentation.

Preferred

• Experience modifying model architectures, heads, loss functions or training pipelines.
• Exposure to MLOps, experiment tracking and model optimisation.