Machine Learning Engineer

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

Interested candidates, who wish to apply for the advertised position, please click on "Apply Now". We regret that only shortlisted candidates will be notified.

EA License No.: 01C4394

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