Azure AI Engineer: Build Scalable, Responsible AI Solutions

Tasq Work; Taguig; On-site; PHP 1,000,000 - 1,600,000; Full time

Job summary

Tasq Work is seeking an Azure AI Engineer in the Philippines to design, develop, and deploy intelligent solutions using Azure Machine Learning and Cognitive Services. This role emphasizes building scalable, secure, and responsible AI apps that meet business needs.

You will collaborate with data engineers, analysts, and business stakeholders to translate requirements into AI-driven solutions, ensure alignment with enterprise standards, and monitor performance and costs across workloads.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• Experience in designing and deploying AI/ML solutions on Azure.
• Proficiency in Python and Azure SDKs for machine learning and cognitive services.
• Strong understanding of AI/ML fundamentals, including model training, evaluation, and deployment.
• Familiarity with cloud-native development and CI/CD practices for ML workflows.
• Excellent communication and collaboration skills.

Responsibilities

• AI Solution Development: Design and deploy AI solutions using Azure ML pipelines and SDKs.
• Collaboration & Business Alignment: Translate business requirements into AI-driven solutions with stakeholders.
• Responsible AI & Governance: Apply responsible AI principles, ensuring fairness and privacy.
• Monitoring & Optimization: Monitor workloads with Azure Monitor and optimize performance and costs.

Skills

Python

Azure AI

Azure ML

CI/CD for ML

Communication

Education

Bachelor's degree in Computer Science, Engineering, or a related field

Tools

Azure ML Studio

Azure SDKs

Azure AI Services

Power BI

Job description

Tasq Work is seeking an Azure AI Engineer in the Philippines to design, develop, and deploy intelligent solutions using Azure Machine Learning and Cognitive Services. This role emphasizes building scalable, secure, and responsible AI apps that meet business needs.

You will collaborate with data engineers, analysts, and business stakeholders to translate requirements into AI-driven solutions, ensure alignment with enterprise standards, and monitor performance and costs across workloads.