We are seeking a skilled professional to design, develop, and deploy AI-driven solutions using Microsoft's AI ecosystem. This role focuses on leveraging Azure Machine Learning, Azure Cognitive Services, and related tools to build scalable, secure, and responsible AI applications that enhance business processes and customer experiences.
Key Responsibilities:
AI Solution Development
- Design and implement AI solutions using Azure Machine Learning, Azure AI Studio, and Azure Cognitive Services.
- Develop and train machine learning models for predictive analytics, NLP, and computer vision tasks using Python and Azure ML pipelines.
- Integrate prebuilt AI capabilities (Vision, Language, Speech, Document Intelligence) and conversational AI (Bot Framework, Azure OpenAI Service) into enterprise applications
Collaboration & Business Alignment
- Work closely with data scientists, engineers, and business stakeholders to define AI use cases and translate business requirements into AI-driven solutions.
- Participate in solution architecture discussions to ensure scalability and alignment with enterprise standards.
Responsible AI & Governance
- Apply Responsible AI principles, ensuring fairness, transparency, and accountability in AI models.
- Ensure compliance with data privacy, security, and governance standards across AI workloads.
Monitoring & Optimization
- Monitor AI workloads using Azure Monitor, Application Insights, and MLOps best practices.
- Continuously optimize model performance, cost-efficiency, and reliability.
Innovation & Best Practices
- Stay updated on Microsoft AI advancements, including Generative AI and Azure OpenAI Service.
- Promote ethical AI practices and contribute to continuous improvement initiatives.
Required Skills & Qualifications:
- Bachelor's degree in Computer Science, Data Science, Engineering, or related field.
- 3+ years of experience in AI/ML development using Microsoft technologies.
- Strong programming skills in Python, with hands‑on experience using PySpark for large‑scale data processing and ML feature engineering.
- Proficiency in Azure Machine Learning, Azure Cognitive Services, and Power Platform AI capabilities.
- Experience with data preprocessing, model deployment, and MLOps (Azure DevOps, GitHub Actions, MLflow).
- Knowledge of cloud architecture, API integration, and security best practices.
- Excellent analytical, problem-solving, and communication skills.
Preferred Qualifications:
- Microsoft Certified: Azure AI Engineer Associate or Azure Data Scientist Associate.
- Experience with Generative AI, Azure OpenAI Service, and Conversational AI.
- Familiarity with Azure AI Studio, AutoML, and Responsible AI frameworks.
- Knowledge of Power BI for integrating AI insights into dashboards.
