Data Scientist

Job Description

About the Company We are seeking a highly skilled Senior AI/ML Engineer to join our team in a hybrid (offshore) role. The ideal candidate will have a strong background in machine learning engineering, particularly with the Databricks ML stack, Python, and ML Ops. This role focuses on developing, deploying, and maintaining high-performance machine learning models. Experience with Azure Cognitive Services, Azure OpenAI, and AI governance will be an added advantage. About the Role The Senior AI/ML Engineer will be responsible for various aspects of machine learning development, ML Ops, model performance, Azure integration, AI governance, and collaboration with cross-functional teams. Responsibilities Machine Learning Development: Design, develop, and deploy machine learning models using the Databricks ML stack. Write efficient and scalable code in Python for model training and evaluation. Implement feature engineering, data preprocessing, and model tuning techniques to enhance model performance. ML Ops: Establish and manage ML Ops pipelines for continuous integration and continuous deployment (CI/CD) of machine learning models. Automate model training, testing, and deployment processes to ensure robust and reliable model performance. Monitor and maintain deployed models to ensure they meet performance and reliability standards. Model Performance: Conduct rigorous testing and validation of machine learning models to ensure accuracy, efficiency, and scalability. Utilize performance metrics to assess model effectiveness and make data-driven improvements. Collaborate with data scientists and engineers to troubleshoot and resolve model performance issues. Azure Integration: Integrate machine learning models with Azure services, leveraging tools like Azure Cognitive Services and Azure OpenAI. Utilize Azure resources for model training, deployment, and management. Explore and implement AI solutions using Azure's advanced capabilities. AI Governance: Ensure compliance with AI governance policies and best practices. Implement ethical AI practices and contribute to the development of governance frameworks. Monitor and address potential biases and ethical concerns in machine learning models. Collaboration and Coordination: Work closely with cross-functional teams, including data scientists, engineers, and business stakeholders. Coordinate with offshore teams to ensure seamless collaboration and project alignment. Participate in team meetings, providing insights and updates on project progress. Required Skills Strong background in machine learning engineering, particularly with the Databricks ML stack, Python, and ML Ops.,Rag,GenAI,Chatbot