Description GSPANN is hiring an experienced AI Developer to build AI-driven applications, scalable Machine Learning (ML) solutions, and data pipelines. Expertise in Python, ML frameworks (Scikit-learn, PyTorch, TensorFlow), and Azure AI services, including Azure OpenAI, Azure AI Foundry, and Microsoft Copilot Studio, is required.
Role and Responsibilities
- Design, develop, and maintain AI-driven applications using Microsoft Copilot Studio and Azure AI Foundry.
- Collaborate with data scientists and engineers to operationalize machine learning models into scalable business solutions.
- Build and optimize data pipelines tailored for AI workloads.
- Deploy AI models and ensure they meet performance, reliability, and scalability requirements.
- Create application programming interfaces (APIs) and integrations that connect AI solutions with core business applications.
- Implement monitoring and automation to maintain AI systems in production environments.
- Engage with business stakeholders to understand use cases and deliver impactful AI-powered solutions.
- Document methodologies and share best practices to enable cross-team knowledge sharing.
Skills and Experience
Hold a master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.Certification in cloud-based AI services, machine learning, or MLOps provide an added advantage.Demonstrate proven experience in data engineering, AI solution development, and ML model deployment.Write efficient code in Python and work effectively with ML frameworks such as Scikit-learn, PyTorch, and TensorFlow.Leverage Azure AI services, including Azure OpenAI, Azure AI Foundry, and Microsoft Copilot Studio, to develop robust solutions.Build and manage data pipelines, apply Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes, and use orchestration tools such as Azure Data Factory (ADF), Databricks, and Azure Synapse.Knowledge of Azure Fabric or Apache NiFi is advantageous.Develop APIs, design microservices, and implement cloud-based architectures.Apply Machine Learning Operations (MLOps) principles, manage Continuous Integration / Continuous Deployment (CI / CD) pipelines, and oversee model lifecycle management.Work with structured and unstructured datasets, including text, images, and other complex data types.Translate business requirements into effective technical solutions by applying strong problem-solving skills