AI ML/Integration Engineer | ASAP NEEDED

Shearwater Health; Philippines; On-site; PHP 900,000 - 1,400,000; Full time

Job summary

Shearwater Health is seeking an ML Integration Engineer to deploy ML models across enterprise systems and build scalable APIs. You will collaborate with Data Science, Engineering, and DevOps teams to ensure secure, governed AI solutions aligned with business needs.

You will design/implement CI/CD for ML, optimize performance, and deploy on cloud platforms while maintaining thorough documentation and governance.

Qualifications

• Graduate or Master’s Degree in Information Technology, Computer Science, Engineering with at least 2+ years in healthcare settings.
• Bachelor's or Master's in Computer Science, Information Technology, AI, or related field.
• 3–8 years of software development, ML engineering, or AI integration experience.

Responsibilities

• Integrate Machine Learning models into web, mobile, and enterprise applications.
• Design and develop APIs and microservices to expose ML model capabilities.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, and DevOps teams to deploy AI solutions.
• Build and maintain CI/CD pipelines for ML model deployment (MLOps).
• Optimize model inference performance, latency, and scalability.
• Deploy ML solutions on cloud platforms such as AWS, Azure, or Google Cloud.
• Monitor production ML systems for performance, availability, and model drift.
• Troubleshoot integration issues and improve system reliability.
• Implement security controls for AI applications, including authentication, authorization, and data privacy.
• Integrate AI services such as LLMs, Generative AI, NLP, and Computer Vision into business applications.
• Develop automation workflows using APIs, event-driven architecture, and messaging platforms.
• Maintain technical documentation, deployment guides, and architecture diagrams.
• Ensure compliance with enterprise security, governance, and regulatory requirements

Skills

Python

Java

Node.js

APIs/REST

ML deployment

CI/CD

Cloud platforms

Security/compliance

Education

Bachelor/Master in CS/IT/AI

Healthcare experience

Tools

Docker

Kubernetes

Jira

Azure DevOps

GitHub Actions

SQL/NoSQL

Job description

The ML Integration Engineer enables the seamless deployment of Machine Learning solutions across the enterprise by integrating models into production systems, building scalable APIs, and automating end-to-end MLOps workflows. The role ensures that AI capabilities are reliable, secure, and aligned with business requirements by collaborating with Data Science, Engineering, and DevOps teams, validating solutions, and maintaining strong governance and documentation standards.

Core Responsibilities:

• Integrate Machine Learning models into web, mobile, and enterprise applications.

• Design and develop APIs and microservices to expose ML model capabilities.

• Collaborate with Data Scientists, ML Engineers, Software Engineers, and DevOps teams to deploy AI solutions.

• Build and maintain CI/CD pipelines for ML model deployment (MLOps).

• Optimize model inference performance, latency, and scalability.

• Deploy ML solutions on cloud platforms such as AWS, Azure, or Google Cloud.

• Monitor production ML systems for performance, availability, and model drift.

• Troubleshoot integration issues and improve system reliability.

• Implement security controls for AI applications, including authentication, authorization, and data privacy.

• Integrate AI services such as Large Language Models (LLMs), Generative AI, NLP, and Computer Vision into business applications.

• Develop automation workflows using APIs, event-driven architecture, and messaging platforms.

• Maintain technical documentation, deployment guides, and architecture diagrams.

• Ensure compliance with enterprise security, governance, and regulatory requirements

Qualifications:

• Graduate or Master’s Degree with 5 years in Information technology, Computer science Engineering with at least 2+ years in healthcare (CPO/BPO, payer, provider, or health tech).

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, or a related field.

• 3–8 years of experience in software development, ML engineering, or AI integration.

• Strong programming skills in Python, Java, C#, or Node.js.

• Experience integrating RESTful APIs, GraphQL, or gRPC services.

• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

• Knowledge of containerization using Docker and Kubernetes.

• Experience with CI/CD tools such as GitHub Actions, Azure DevOps, Jenkins, or GitLab CI.

• Familiarity with cloud platforms (AWS, Azure, or Google Cloud).

• Experience with databases including SQL and NoSQL.

• Strong understanding of software architecture, distributed systems, and microservices

• Tools: - Jira, Azure services, Confluence, Microsoft Visio, Microsoft Excel, Power BI, Tableau

Skills You'll Bring:

• PMP, PRINCE2, Agile / Scrum Certifications, ITIL and Lean Six Sigma

• Familiarity with productizing AI/ML and agentic systems in healthcare operations

• Programming: Python, Java, C#, JavaScript/TypeScript

• Frameworks: TensorFlow, PyTorch, Scikit-learn, Fast API, Flask

• Cloud: AWS, Azure, Google Cloud Platform

• Containers: Docker, Kubernetes

• Version Control: Git, GitHub, Azure DevOps

• CI/CD: Jenkins, GitHub Actions, GitLab CI

• Databases: PostgreSQL, MySQL, MongoDB, Redis

• Messaging: Kafka, RabbitMQ

• Monitoring: Prometheus, Grafana, ELK Stack