Job Description & How to Apply Below
- Build and optimize data pipelines for training and inference using Azure Data Factory, Azure Synapse, and Databricks.
- Collaborate with data scientists, engineers, and business stakeholders to translate requirements into scalable AI solutions.
- Implement MLOps practices for model versioning, monitoring, and continuous deployment.
- Ensure solutions meet performance, scalability, and security standards within Azure cloud environments.
- Stay updated on emerging AI technologies and recommend adoption strategies.
- 4–5 years of experience in AI/ML development, with at least 3 years working on Azure AI ecosystem and exposure to Google Cloud AI/ML services.
- Proficiency in Python, R, or C# for AI/ML development.
- Hands-on experience with Azure Machine Learning Studio, Azure Cognitive Services (Vision, Speech, Language, Decision), and Azure OpenAI Service.
- Strong understanding of MLOps, CI/CD pipelines, and containerization (Docker, Kubernetes).
- Experience with data engineering tools (Azure Data Factory, Synapse, Databricks).
- Knowledge of cloud security, compliance, and cost optimization best practices
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