ML Engineer: Deploy & Optimize Production Models (Hybrid)

HRTx Inc.; Mandaluyong; Hybrid; PHP 600,000 - 900,000; Full time

Benefits offered by this job

Health insurance

Job summary

HRTx Inc. is seeking a Machine Learning Engineer to research, train, optimize, and deploy scalable ML models into production systems.

The role includes building, training, and evaluating algorithms, collaborating with data engineers and scientists on data pipelines, and monitoring model performance in production. The candidate should have 3–5 years of ML engineering experience, proficiency in Python or R, and experience with frameworks like TensorFlow, PyTorch, or Scikit-learn, plus cloud ML

Qualifications

• 3–5 years of practical experience in ML engineering and model deployment.
• Proficiency in Python or R and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with cloud ML platforms (AWS SageMaker, Google AI Platform, or equivalent).

Responsibilities

• Build, train, and evaluate ML algorithms for performance, accuracy, and scalability.
• Collaborate with data engineers and scientists to prepare datasets and feature pipelines.
• Monitor deployed model performance, drift, and operational health.

Skills

Python

ML deployment

Tools

TensorFlow

PyTorch

Scikit-learn

AWS SageMaker

Google AI Platform

Job description

HRTx Inc. is seeking a Machine Learning Engineer to research, train, optimize, and deploy scalable ML models into production systems.

The role includes building, training, and evaluating algorithms, collaborating with data engineers and scientists on data pipelines, and monitoring model performance in production. The candidate should have 3–5 years of ML engineering experience, proficiency in Python or R, and experience with frameworks like TensorFlow, PyTorch, or Scikit-learn, plus cloud ML