AI Deployment Engineer: Scalable Production ML Systems

Hammerjack Pty Ltd; Philippines; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

Hammerjack Pty Ltd is seeking an experienced AI deployment lead in the Philippines to oversee the rollout of AI-based applications across multiple operational workflows. You will drive end-to-end integration of AI models into production systems, ensuring reliability, scalability, and safety.

The role requires collaboration with cross-functional teams to identify deployment opportunities, and ongoing monitoring and tuning of deployed AI systems to maintain performance standards.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Software Engineering, or related field.
• 3+ years deploying and managing AI/ML applications in production.
• Must possess full-stack development skills and Linux deployment proficiency.
• Proficiency in Python, API integration, and cloud-based AI deployment with CI/CD pipelines and model monitoring.

Responsibilities

• Scope and lead the deployment of AI-based applications across operational workflows.
• Manage end-to-end integration of AI models into production systems, ensuring reliability and scalability.
• Collaborate with cross-functional teams to identify and execute AI deployment opportunities.
• Monitor, maintain, and optimize deployed AI systems to ensure performance and safety standards.

Skills

Full-stack development

Linux proficiency

Python

API integration

CI/CD pipelines

Model monitoring

AI deployment experience

Education

Bachelor's or Master's in Computer Science/AI/Software Engineering

Job description

Hammerjack Pty Ltd is seeking an experienced AI deployment lead in the Philippines to oversee the rollout of AI-based applications across multiple operational workflows. You will drive end-to-end integration of AI models into production systems, ensuring reliability, scalability, and safety.

The role requires collaboration with cross-functional teams to identify deployment opportunities, and ongoing monitoring and tuning of deployed AI systems to maintain performance standards.