AI/Machine Learning Engineer

Hitachi Digital Payment Solutions Philippines Inc.; Makati; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

Hitachi Digital Payment Solutions Philippines Inc. is seeking a hands-on AI/ML Engineer to take ideas from concept to deployment, designing, training, and integrating models into core systems.

You will work across data science, software engineering, and MLOps to deliver end-to-end AI solutions that support business objectives. You will develop and deploy ML models, ensure scalable inference, and monitor performance.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or related field.
• 3+ years of applied ML or AI engineering experience.
• Strong proficiency in Python and TensorFlow, PyTorch, or Scikit-learn.
• Experience building and deploying APIs (FastAPI, Flask, Node).
• Familiarity with cloud services (AWS, GCP, Azure) or containerization (Docker, Kubernetes).
• Practical knowledge of data pipelines (ETL, data versioning, labeling tools).
• Strong understanding of model evaluation and performance tuning.

Responsibilities

• Collect, clean, and preprocess data for training and testing.
• Design and develop machine learning models (classical ML or deep learning).
• Train, tune, and validate models using real-world datasets.
• Develop APIs or services to integrate the model into the main product or platform.
• Collaborate with backend and frontend developers to embed AI functionality.
• Ensure efficient inference and scalability in production environments.
• Package and deploy models (e.g., via Docker, FastAPI, or cloud ML services).
• Set up monitoring for model accuracy, drift, and system performance.
• Document models, datasets, and architecture decisions.
• Communicate findings and results clearly to non-technical stakeholders.

Skills

Python

TensorFlow

PyTorch

Scikit-learn

API development

Cloud services

Docker & Kubernetes

Data pipelines

Model evaluation

Performance tuning

Education

Bachelor’s or Master’s in Computer Science / Data Science / AI/ML

Tools

FastAPI

Flask

Node

Docker

Kubernetes

Pinecone/FAISS/Milvus

Job description

About the Role

We are looking for a hands-on AI/ML Engineer who can take an idea from concept to deployment. You will be responsible for designing, developing, training, testing, and integrating machine learning models into core systems.

This role requires a versatile professional skilled in data science, software engineering, and MLOps to deliver end-to-end AI solutions that support business objectives.

Key Responsibilities

Data & Model Development

• Collect, clean, and preprocess data for training and testing.

• Design and develop machine learning models (classical ML or deep learning).

• Train, tune, and validate models using real-world datasets.

• Conduct performance testing and error analysis.

System Integration

• Develop APIs or services to integrate the model into the main product or platform.

• Collaborate with backend and frontend developers to embed AI functionality.

• Ensure efficient inference and scalability in production environments.

MLOps & Deployment

• Package and deploy models (e.g., via Docker, FastAPI, or cloud ML services).

• Set up monitoring for model accuracy, drift, and system performance.

• Maintain version control for models and data pipelines.

Collaboration & Documentation

• Work closely with the Product Manager to translate business goals into technical solutions.

• Document models, datasets, and architecture decisions.

• Communicate findings and results clearly to non-technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.

• 3+ years of experience in applied machine learning or AI engineering.

• Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn.

• Experience building and deploying APIs (e.g., FastAPI, Flask, Node).

• Familiarity with cloud services (AWS, GCP, Azure) or containerization (Docker, Kubernetes).

• Practical knowledge of data pipelines (ETL, data versioning, labeling tools).

• Strong understanding of model evaluation and performance tuning.

Bonus Skills

• Experience with LLMs, prompt engineering, or LangChain.

• Familiarity with vector databases (Pinecone, FAISS, Milvus).

• Exposure to frontend frameworks (React, Vue) for prototyping.

• Understanding of data security and compliance in regulated domains (e.g., fintech, healthcare).

What We Offer

• Opportunity to develop and deploy AI solutions end-to-end.

• Autonomy in technical design and implementation.

• Direct impact on key business initiatives.

• Collaborative environment with continuous learning opportunities.