Job Title

Job Description: Lead the design, development, and deployment of production-level machine learning models, with a focus on generative AI models such as Large Language Models (LLMs), Generative Adversarial Networks (GANs), and Variational Autoencoders (VAEs). Provide advanced technical support for existing AI models, including bug fixes, addressing complex issues, and facilitating model expansion for new business cases. Act as a liaison between data scientists, cloud engineers, data engineers, and the business team to diagnose and resolve issues related to model performance and deployment. Lead the continuous improvement of support processes and workflows for ML applications. Develop, monitor, and maintain end-to-end machine learning pipelines (MLOps) including data preparation, feature engineering, model training, and deployment. Utilize Azure AI Foundry to build, test, and deploy cutting-edge AI-driven solutions and generative AI applications. Build model performance benchmarking, evaluation, and monitoring capabilities. Assess model performance to understand bugs, inefficiencies, and their root cause. Document and communicate best practices and troubleshooting procedures to support teams and stakeholders. Coordinate and mentor the Machine Learning Engineering team, promoting best practices and code quality. Stay current with the latest advancements in AI and machine learning technologies to provide informed support and recommendations.