Machine Learning Engineer (Hybrid) | Mandaluyong

Machine Learning Engineer

Location: Mandaluyong

Work Schedule: Hybrid (3 days Onsite; 2 days WFH)

Role Overview

The Machine Learning Engineer develops and implements machine learning models, optimizes algorithms, and conducts experiments to improve performance and accuracy. This role leverages ML algorithms, data preprocessing, and model training to develop and deploy AI solutions.

Key Responsibilities

• Develop and deploy machine learning models
• Optimize algorithms for performance and scalability
• Conduct experiments and analyze results to improve models
• Collaborate with data scientists to prepare datasets
• Monitor and maintain the performance of deployed models
• Document model development processes and results
• Stay updated on the latest machine learning techniques and tools

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is a plus
• 3–5 years of experience in machine learning and model development
• Proficiency with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Knowledge of data preprocessing and feature engineering
• Experience with model evaluation and optimization techniques
• Strong programming skills in Python or R
• Familiarity with cloud-based machine learning platforms (e.g., AWS SageMaker, Google AI Platform)