
Solution Architect
1 day ago
Roles and Responsibilities
- Design, develop, and deploy AI/ML models using Microsoft Azure AI services (e.g., Azure Machine Learning, Cognitive Services, OpenAI on Azure).
- Collaborate with stakeholders to translate business challenges into AI-based solutions.
- Lead end-to-end AI projects: from data collection and preprocessing to model training, evaluation, and deployment.
- Integrate open-source frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) into Microsoft cloud environments.
- Optimize AI pipelines using MLOps tools (e.g., Azure ML Pipelines, GitHub Actions, MLflow).
- Develop data science models for predictive analytics, NLP, computer vision, or generative AI applications.
- Champion responsible AI practices, data governance, model fairness, and transparency.
- Mentor junior data scientists and engineers; conduct code reviews and knowledge-sharing sessions.
Required Qualifications:
- 10+ years of experience in AI, machine learning, or data science roles.
- Strong experience with Microsoft AI/ML stack: Azure Machine Learning, Azure Cognitive Services, Power BI with AI, Azure Synapse Analytics.
- Proficiency in open-source AI frameworks: TensorFlow, PyTorch, Hugging Face, Scikit-learn.
- Strong programming skills in Python (preferred), R, or C#.
- Deep understanding of data modeling, statistical analysis, and algorithm development.
- Experience with cloud-native AI deployments and containerization (Docker, Kubernetes).
- Hands-on knowledge of MLOps, CI/CD pipelines, and AI lifecycle management.
- Experience working in agile and cross-functional teams.
- Excellent communication, leadership, and presentation skills.
Preferred Qualifications:
Microsoft certifications such as:
Azure AI Engineer Associate
- Azure Data Scientist Associate
Azure Solutions Architect Expert
Experience integrating AI into Microsoft Power Platform and Dynamics 365.
- Exposure to generative AI (e.g., OpenAI, GPT models on Azure, LLM fine-tuning).
- Experience in multi-cloud or hybrid-cloud AI architecture.
- Familiarity with open-source data versioning and pipeline tools (e.g., DVC, Kedro, Prefect).
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