Machine Learning Engineer | Hybrid Setup

Work Setup: Monday to Friday, Hybrid (2 days onsite, 3 days wfh) Location: Mandaluyong Key Responsibilities: Develop, implement, and deploy machine learning models to support AI solution development. Optimize machine learning algorithms to enhance performance, efficiency, and scalability. Conduct experiments and evaluate results to improve model accuracy and overall performance. Collaborate with data scientists to prepare datasets and support data preprocessing activities. Monitor and maintain deployed models, document development processes and findings, and stay informed about emerging machine learning techniques and tools. Qualifications: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is an advantage. 3–5 years of experience in machine learning and model development. Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Knowledge of data preprocessing, feature engineering, model evaluation, and optimization techniques. Strong programming skills in Python or R, with familiarity with cloud-based machine learning platforms such as AWS SageMaker or Google AI Platform.