Machine Learning Engineer (Hybrid Setup)
Work Setup: Monday to Friday, Hybrid (2 days onsite, 3 days wfh)
Location: Mandaluyong
Key Responsibilities:
Design, build, and implement machine learning models for AI-driven applications and solutions.
Refine algorithms and model architectures to improve efficiency, scalability, and overall performance.
Perform experiments, assess model outcomes, and identify opportunities to enhance accuracy and reliability.
Work closely with data scientists to prepare, process, and organize datasets for model development.
Track and maintain deployed model performance, document technical processes and findings, and keep up with advancements in machine learning technologies and methodologies.
Qualifications:
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related discipline; a Master’s degree is preferred but not required.
3–5 years of professional experience in machine learning and developing predictive or analytical models.
Hands-on experience with machine learning libraries and frameworks, including TensorFlow, PyTorch, or Scikit-learn.
Understanding of data preparation, feature engineering, model assessment, and techniques for improving model performance.
Proficiency in Python or R, with working knowledge of cloud-based machine learning services such as AWS SageMaker or Google AI Platform.
Employer questions
- What's your expected monthly basic salary?
- How many years' experience do you have as a Machine Learning Engineer?
- Which of the following types of qualifications do you have?
- Have you worked in a role which requires experience with machine learning?
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