Machine Learning Specialist (Research & Engineering)

Indra Philippines, Inc.; Philippines; On-site; PHP 900,000 - 1,500,000; Full time

Job summary

Indra Philippines, Inc. seeks a seasoned ML researcher/engineer to advance state-of-the-art architectures and foundational models. You will design experimentation datasets, production data pipelines, and oversee end-to-end model deployment with Docker and Kubernetes.

In a cross-functional squad, you will collaborate with Data Engineers, Backend Developers, and Product Owners to ensure seamless product integration, document the full tech stack, and champion explainability and security.

Qualifications

• Undergraduate degree in a quantitative field; Master/PhD preferred for research.
• 3+ years in data science, ML research, or ML engineering.
• Expert-level Python and SQL.
• Strong experience with ML frameworks (PyTorch, TensorFlow, JAX).
• Hands-on with Git, CI/CD and MLOps tools.
• Bias toward model explainability and security.

Responsibilities

• Conduct deep-dive research into SOTA architectures and foundational models.
• Lead design of experimentation datasets and production data pipelines; focus on feature engineering and augmentation.
• Architect and manage end-to-end deployment of models using containers (Docker, Kubernetes) and CI/CD pipelines.
• Collaborate in a cross-functional squad with Data Engineers, Backend Developers, and Product Owners for seamless integration.
• Author and maintain full technical stack documentation from research findings to deployment guides.

Skills

Python

SQL

PyTorch

TensorFlow

JAX

Git

CI/CD

MLOps

Model explainability

Security mindset

Education

Bachelor's degree in a quantitative field

Master's or PhD preferred for research

Tools

Docker

Kubernetes

CI/CD pipelines

Git

Job description

Research & Experimental Innovation

Advanced Research: Conduct deep-dive research into state-of-the-art (SOTA) architectures and foundational models to solve complex business problems like credit scoring, fraud detection and personalization.

Data Strategy & Engineering

Pipeline Design: Lead the design of experimentation datasets and production data pipelines, focusing on feature engineering and data augmentation.

Production Engineering & MLOps

Deployment & Orchestration: Architect and manage the end-to-end deployment of models using containers (Docker, Kubernetes) and CI/CD pipelines.

Squad Collaboration & Agile Delivery

Active Squad Collaboration: Work as a core member of a cross-functional squad, aligning daily with Data Engineers, Backend Developers, and Product Owners to ensure seamless product integration.

Documentation & Knowledge Leadership

Technical Documentation: Author and maintain the full technical stack documentation, ranging from scientific research findings and experimental logs to system architecture diagrams and deployment guides.

Qualifications

Education: Undergraduate degree in a quantitative field (e.g. Computer Science, Statistics, Information Technology or Physics or Mathematics). A Graduate degree (Master's or PhD) is highly preferred for the research component.

Experience: 3+ years in a functionally similar role (Data Science , ML Research, or ML Engineering.

Technical Proficiency: Expert-level Python and SQL.

Strong experience with ML frameworks (e.g. Pytorch, TensorFlow, JAX).

Hands-on experience with Git, CI/CD and MLOps tools.

Mindset: A strong bias toward model explainability and security.