Junior Data Scientist: ML Lifecycle, Deployment & GenAI

PLDT INC; Makati; On-site; PHP 1,200,000 - 2,400,000; Full time

Job summary

PLDT INC is seeking an experienced ML/AI professional to lead model development and deployment across on-premises and cloud environments. You will manage data preparation, feature engineering, and deployment while ensuring model performance and reliability.

Candidates should have strong Python/SQL skills, familiarity with AWS/Databricks, and a track record in responsible AI practices. Collaboration with cross‑functional teams is essential for success.

Qualifications

• 2–4+ years’ experience with the full ML/AI lifecycle from data preparation to deployment and monitoring.
• Strong proficiency in Python and SQL, plus experience with AWS/Databricks.
• Clear communication to explain ML concepts to diverse stakeholders.
• Exposure to Generative AI/LLMs and responsible AI practices (bias, data privacy).
• Hands‑on ML pipelines: LLMOps, RAG, or Agentic AI experience.
• Version Control (git) and CI/CD pipelines for ML deployment.

Responsibilities

• Collaborate with data science and engineering to develop, optimize, and deploy models on premises and in cloud.
• Oversee the ML lifecycle from data prep to deployment and monitoring.
• Prepare, clean, and transform data for training and inference.
• Ensure scalability, reliability, and performance of ML models.
• Monitor deployed models, implement updates, and troubleshoot issues.
• Design and maintain ML pipelines for efficient data flow and deployment.
• Translate analytical findings into actionable recommendations.
• Ensure responsible AI practices addressing bias, fairness, and data privacy.

Skills

ML lifecycle experience

Python

SQL

Generative AI/LLMs

LLMOps / RAG / Agentic AI

Git version control

CI/CD for ML

Education

Bachelor’s degree in quantitative field

Tools

AWS

Databricks

Job description

PLDT INC is seeking an experienced ML/AI professional to lead model development and deployment across on-premises and cloud environments. You will manage data preparation, feature engineering, and deployment while ensuring model performance and reliability.

Candidates should have strong Python/SQL skills, familiarity with AWS/Databricks, and a track record in responsible AI practices. Collaboration with cross‑functional teams is essential for success.