AI/ML Engineer

Full Job Description

We are seeking a hands-on, versatile AI/ML Engineer (Full-Stack Machine Learning Developer) to join our team on a full-time, project-based arrangement. In this role, you will take AI/ML concepts from initial design to production deployment, serving as the bridge between data science, software engineering, and MLOps to deliver end-to-end AI solutions.

Key Responsibilities

Data & Model Development

• Collect, clean, and preprocess data for training and testing.
• Design and develop machine learning models using classical ML or deep learning approaches.
• Train, tune, and validate models using real-world datasets.
• Conduct performance testing and detailed error analysis.

System Integration

• Develop robust APIs or microservices to integrate ML models into our core platform.
• Collaborate with backend and frontend developers to embed AI functionality seamlessly.
• Ensure high-efficiency inference and system scalability in production environments.

MLOps & Deployment

• Package and deploy models using tools such as Docker, FastAPI, or cloud ML infrastructure.
• Establish monitoring systems for model accuracy, data drift, and overall system performance.
• Maintain strict version control for models, code, and data pipelines.

Collaboration & Documentation

• Work closely with Product Managers to translate business objectives into technical architectures.
• Document model specifications, dataset structures, and architectural decisions.
• Communicate findings and complex metrics clearly to non-technical stakeholders.

Qualifications & Requirements

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• Experience: 3+ years of hands-on experience in applied machine learning or AI engineering.
• Core Technical Skills:
• Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Practical understanding of model evaluation, hyperparameter tuning, and error analysis.
• Experience with data pipelines (ETL, data versioning, labeling tools).
• Infrastructure & Cloud: Familiarity with cloud services (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).

Nice-to-Have Skills

• Experience building applications with Large Language Models (LLMs), prompt engineering, or LangChain.
• Experience with vector databases (e.g., Pinecone, FAISS, Milvus).
• Exposure to modern frontend frameworks (e.g., React, Vue) for rapid prototyping.
• Understanding of data security and compliance standards in regulated domains (e.g., fintech, healthcare).

Benefits & Work Setup

• Work Setup: Hybrid (combination of remote and on-site days).
• Employment Structure: Full-time, Project-based.
• Salary: ₱70,000.00 – ₱100,000.00 per month (commensurate with experience).
• Direct impact on core business initiatives with full autonomy over technical design and execution.
• Collaborative environment prioritizing continuous learning and innovation.

Pay: Php70,000.00 - Php100,000.00 per month

Application Question(s):

• How many years of experience do you have in developing and deploying applied machine learning models to production environments?
• Which ML/DL frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and deployment tools (e.g., FastAPI, Docker) are you most proficient in using?
• Can you briefly describe a project where you took an ML model all the way from raw data preprocessing to API integration and production deployment?
• Do you have hands-on experience working with LLMs, vector databases (e.g., Pinecone, FAISS), or frameworks like LangChain? If so, please highlight a brief example.
• Are you comfortable with a full-time, project-based contract under a hybrid work model, and what is your standard notice period?

Work Location: Hybrid remote in Makati