ML & AI Integration Engineer (Cloud, Microservices)

Our Clients; Taguig; On-site; PHP 900,000 - 1,200,000; Full time

Job summary

Our Clients is seeking an experienced software/ ML engineer to design and implement AI-enabled solutions for healthcare environments. You will work across the stack from data processing to model deployment, collaborating with teams on RESTful and GraphQL integrations, containerized services, and CI/CD pipelines.

The role requires hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), cloud platforms (AWS/Azure/Google Cloud), and distributed systems.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, AI, Engineering, or related field.
• 3–8 years of experience in software development, ML engineering, or AI integration.
• At least 2 years of experience in healthcare industry (healthtech/BPO/ payer/provider).
• Strong programming skills in Python, Java, C#, or Node.js.
• Experience integrating RESTful APIs, GraphQL, or gRPC services.
• Hands-on AI/ML development with TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of Docker and Kubernetes.
• Experience with CI/CD tools: GitHub Actions, Azure DevOps, Jenkins, GitLab CI.
• Familiarity with AWS, Azure, or Google Cloud.
• Experience with SQL and NoSQL databases.
• Strong understanding of software architecture, distributed systems, and microservices.

Skills

Python

Java

C#

Node.js

RESTful APIs

GraphQL

gRPC

AI/ML development

Docker

Kubernetes

CI/CD

AWS

Azure

Google Cloud

SQL

NoSQL

Distributed systems

Microservices

Education

Bachelor's or Master's degree in CS/IT/AI or related field

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

GitHub Actions

Azure DevOps

Jenkins

GitLab CI

AWS

Azure

Google Cloud

SQL

NoSQL

Job description

Our Clients is seeking an experienced software/ ML engineer to design and implement AI-enabled solutions for healthcare environments. You will work across the stack from data processing to model deployment, collaborating with teams on RESTful and GraphQL integrations, containerized services, and CI/CD pipelines.

The role requires hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), cloud platforms (AWS/Azure/Google Cloud), and distributed systems.