Microsoft Azure AI Engineer
Gratitude IncMicrosoft Azure AI Engineer
Job Description
Key Skills
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Job Overview
We are looking for a skilled Microsoft Azure AI Engineer to design, develop, and deploy intelligent AI/ML solutions using Microsoft Azure. The role focuses on building scalable, secure, and responsible AI applications using Azure Machine Learning, Azure AI Studio, and Azure AI Services.
The ideal candidate should have strong hands-on experience in AI/ML, Microsoft Azure, Python, Azure Machine Learning, Azure AI Services, model development and deployment, along with a good understanding of MLOps, cloud-native development, and responsible AI practices.
Key Responsibilities
AI Solution Development
Design, develop, and deploy AI/ML solutions using Azure Machine Learning, Azure AI Studio, and Azure AI Services.
Build and deploy Python-based machine learning models using Azure ML pipelines and SDKs.
Integrate prebuilt Azure AI capabilities such as Vision, Language, Speech, and Document Intelligence into enterprise applications.
Develop scalable and reliable AI solutions aligned with business requirements.
Support model training, evaluation, deployment, and optimization.
Collaboration & Business Alignment
Work closely with data engineers, data analysts, developers, and business stakeholders.
Translate business requirements into practical AI/ML solutions.
Participate in solution architecture and technical design discussions.
Ensure AI solutions align with enterprise architecture, scalability, security, and development standards.
Collaborate with cross-functional teams throughout the AI solution lifecycle.
Responsible AI & Governance
Apply Responsible AI principles throughout AI/ML development and deployment.
Promote fairness, transparency, accountability, and responsible use of AI models.
Ensure AI workloads follow applicable data privacy, security, and governance requirements.
Support secure and compliant implementation of AI solutions.
Monitoring & Optimization
Monitor deployed AI/ML workloads using Azure Monitor and Application Insights.
Identify and troubleshoot performance, reliability, and deployment issues.
Optimize model performance, resource utilization, cost efficiency, and reliability.
Apply MLOps best practices to improve the lifecycle management of machine learning solutions.
Required Qualifications & Experience
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
Minimum 3 years of professional experience in AI/ML.
Hands-on experience designing and deploying AI/ML solutions on Microsoft Azure.
Strong proficiency in Python.
Experience with Azure SDKs and machine learning services.
Strong understanding of AI/ML fundamentals, including:
Model training
Model evaluation
Model deployment
Machine learning workflows
Experience with Azure Machine Learning.
Understanding of cloud-native application development.
Familiarity with CI/CD practices for ML workflows.
Strong communication, analytical, and collaboration skills.
Preferred Skills
Experience with Azure AI Studio.
Experience with Azure ML Designer.
Experience with Azure AutoML.
Knowledge of MLOps practices.
Experience with MLflow.
Experience with Azure DevOps.
Experience with GitHub Actions.
Microsoft Azure AI certifications, such as Azure AI Engineer Associate, are a plus.
Familiarity with Power BI for integrating AI-generated insights into dashboards and business reporting.
Technical Skills
Mandatory / Core Skills:
Microsoft Azure
Azure Machine Learning
Azure AI Services
Azure AI Studio
Python
AI/ML
Machine Learning Models
Model Training & Evaluation
Model Deployment
Azure ML Pipelines
Azure ML SDKs
Cloud-Native Development
Responsible AI
AI Governance
Additional Skills:
Azure Monitor
Application Insights
MLOps
MLflow
Azure DevOps
GitHub Actions
Azure ML Designer
AutoML
Power BI
CI/CD
Data Privacy & Security
Soft Skills
Strong analytical and problem-solving skills.
Excellent communication and interpersonal skills.
Ability to work effectively with technical and business stakeholders.
Strong collaboration and teamwork capabilities.
Ability to understand business requirements and translate them into technical solutions.
Strong attention to detail.
Ability to manage multiple priorities in a fast-paced environment.
Proactive approach to troubleshooting and continuous improvement.
Work Setup & Eligibility
Work Mode: Onsite
Location: Taguig, Philippines
Shift: Shifting
Candidates must currently be located in the Philippines.
Candidates must already have the legal right to live and work in the Philippines.
Candidates must be willing to work onsite in Taguig.
Candidates must be flexible to work in shifting schedules.
Recruitment Process
The recruitment process may include:
Initial screening with CV Reviewer.
Candidate endorsement for validation.
Further CV screening through Workday along with the required HRI toolkit, FCV, and updated CV.
Client review and selection.
Pre-Screening Questions
How many years of professional experience do you have in AI/ML?
How many years of hands-on experience do you have designing or deploying AI/ML solutions on Microsoft Azure?
How would you rate your understanding of AI/ML fundamentals, including model training, evaluation, and deployment?
What was your last drawn salary?
What is your salary expectation?
Are you amenable to working onsite in Taguig with a shifting schedule?
What is your notice period?
Role
Computer Operators
Timings
Rotational Shifts (Contract To Hire)
Industry
IT-Software / Software Services
Work Mode
Work from office
Process
Non-Voice
Functional Area
IT Software/Hardware
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