Machine Learning Engineer | Hybrid Setup
Posted
Summary
Machine Learning Engineer at HRTX developing, deploying, and optimizing ML models for AI solutions — running experiments, preprocessing data with data scientists, and monitoring deployed models. Stack includes TensorFlow/PyTorch/Scikit-learn, Python or R, and cloud ML platforms like AWS SageMaker, on a hybrid schedule.
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.
