Machine Learning Engineer

PERSOL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 120,000 - 160,000; Full time

Job summary

PERSOL SINGAPORE PTE. LTD. is seeking a seasoned ML Engineer to design and deploy machine learning solutions across APAC. You'll build models for recommendations, forecasting, NLP and computer vision, and drive them from prototype to production.

Collaborating with HQ engineering and regional teams, you will own data pipelines, training workflows, and model serving. You will monitor performance, retrain when needed, and contribute to MLOps best practices across regions.

Qualifications

• Bachelor's/Master's in CS, ML, Statistics or related field, or equivalent practical experience.
• Around 3 years of experience building and deploying ML models in production.
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Solid understanding of the full ML lifecycle: data pipelines, feature engineering, training, evaluation, deployment, and monitoring.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
• Strong communication skills and ability to work effectively across cross-border, cross-functional teams.

Responsibilities

• Design, prototype, and build ML models (e.g. recommendation, forecasting, NLP, computer vision).
• Take models from proof-of-concept through to production deployment, including data pipelines, training workflows, and model serving infrastructure
• Collaborate closely with HQ engineering and data science teams on model architecture, data standards, and shared infrastructure
• Work with APAC product, business, and regional engineering teams to gather requirements and localize solutions
• Monitor and maintain model performance in production, including retraining and iteration based on live feedback
• Contribute to MLOps best practices, including CI/CD, model versioning, and experiment tracking
• Communicate technical trade-offs clearly to both technical and business stakeholders across regions and time zones

Skills

Python

PyTorch

TensorFlow

Docker

Kubernetes

Education

Bachelor's or Master's in CS/ML

Tools

AWS

GCP

Azure

Job description

Roles & Responsibilities

• Design, prototype, and build ML models (e.g. recommendation, forecasting, NLP, computer vision)
• Take models from proof-of-concept through to production deployment, including data pipelines, training workflows, and model serving infrastructure
• Collaborate closely with HQ engineering and data science teams on model architecture, data standards, and shared infrastructure
• Work with APAC product, business, and regional engineering teams to gather requirements and localize solutions
• Monitor and maintain model performance in production, including retraining and iteration based on live feedback
• Contribute to MLOps best practices, including CI/CD, model versioning, and experiment tracking
• Communicate technical trade-offs clearly to both technical and business stakeholders across regions and time zones

Requirements

• Bachelor's or Master's Degree in Computer Science, Machine Learning, Statistics, or a related field (or equivalent practical experience)
• Around 3 years of experience building and deploying machine learning models in production environments
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Solid understanding of the full ML lifecycle: data pipelines, feature engineering, training, evaluation, deployment, and monitoring
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes)
• Strong communication skills and ability to work effectively across cross-border, cross-functional teams