Machine Learning Specialist

Indra Group; Metro Manila; On-site; PHP 900,000 - 1,600,000; Full time

Job summary

Indra Group in Manila is seeking a Machine Learning Specialist to design, develop, deploy, and optimize AI and machine learning solutions from research through production. You will collaborate with cross-functional teams to build scalable ML applications, improve model performance, and implement MLOps best practices that deliver business value.

The role focuses on researching state-of-the-art techniques, designing and fine-tuning models for fraud detection, credit scoring, and personalization,

Qualifications

• Bachelor's degree in Computer Science, IT, Statistics, Mathematics, Physics, or related quantitative field.
• 3+ years of experience in Machine Learning Engineering, Data Science, or AI Research.
• Strong programming skills in Python and SQL.
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience building, training, and deploying ML models in production environments.
• Experience with Git, Docker, Kubernetes, CI/CD, and MLOps practices.
• Strong understanding of model evaluation, optimization, explainability, and AI security.
• Excellent analytical, problem-solving, and communication skills.

Responsibilities

• Research and evaluate state-of-the-art machine learning and generative AI techniques.
• Design, develop, fine-tune, and optimize ML models for business use cases (fraud detection, credit scoring, personalization).
• Build and maintain data pipelines, feature engineering processes, and training datasets.
• Deploy and manage ML models using Docker, Kubernetes, CI/CD, and MLOps practices.
• Develop APIs and integrate AI solutions into enterprise applications.
• Monitor model performance, drift detection, and governance.
• Collaborate with Data Engineers, Software Engineers, and Product Owners in an Agile environment.
• Produce technical documentation and share best practices.

Skills

Python

SQL

Analytical thinking

Communication

ML model deployment

Education

Bachelor's degree in Computer Science or related quantitative field

Tools

PyTorch

TensorFlow

JAX

Git

Docker

Kubernetes

CI/CD

MLOps</w>

Job description

We are looking for a Machine Learning Specialist to design, develop, deploy, and optimize AI and machine learning solutions from research through production. You will work with cross-functional teams to build scalable ML applications, improve model performance, and implement MLOps best practices that deliver business value.

Key Responsibilities:

• Research and evaluate state-of-the-art machine learning and generative AI techniques.
• Design, develop, fine-tune, and optimize machine learning models for business use cases such as fraud detection, credit scoring, and personalization.
• Build and maintain data pipelines, feature engineering processes, and training datasets.
• Deploy and manage ML models using Docker, Kubernetes, CI/CD, and MLOps practices.
• Develop APIs and integrate AI solutions into enterprise applications.
• Monitor model performance, implement version control, drift detection, and model governance.
• Collaborate with Data Engineers, Software Engineers, and Product Owners in an Agile environment.
• Produce technical documentation, conduct code reviews, and share best practices with the team.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Statistics, Mathematics, Physics, or a related quantitative field.
• 3+ years of experience in Machine Learning Engineering, Data Science, or AI Research.
• Strong programming skills in Python and SQL.
• Hands‑on experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience building, training, and deploying ML models in production environments.
• Experience with Git, Docker, Kubernetes, CI/CD, and MLOps practices.
• Strong understanding of model evaluation, optimization, explainability, and AI security.
• Excellent analytical, problem-solving, and communication skills.

Nice to Have

• Experience with Generative AI, LLMs, NLP, recommender systems, or graph‑based machine learning.
• Experience with PEFT, LoRA, QLoRA, or other LLM fine‑tuning techniques.
• Knowledge of AWS, Azure, or Google Cloud AI services.
• Master's degree or PhD in a related field.
• Published AI/ML research or open-source contributions.