Chief Machine Learning Architect

11 hours ago


mangalore, India beBeeData Full time

Job TitleData Scientist SpecialistAbout the RoleWe are seeking a skilled Data Scientist to join our team. As a key member of our data science department, you will be responsible for designing and implementing end-to-end ML pipelines for recommendation systems, search ranking, and classification problems.Key Responsibilities:Design and implement robust machine learning models using techniques such as ensemble methods, SVMs, gradient boosting, and neural networks.Build and optimize traditional ML models for complex business applications.Develop time series forecasting models and ranking algorithms for production environments.Implement feature engineering pipelines that handle real-world data noise and edge cases.Create reliable data preprocessing and validation systems to ensure model performance in production.Machine Learning Deployment:Deploy ML models using Docker containerization and REST API frameworks.Implement model serving solutions with proper monitoring and alerting.Build MLOps pipelines for experiment tracking and model registry management.Design scalable data workflows using Apache Airflow for ETL operations.Establish model versioning, rollback strategies, and performance monitoring in production environments.Technical Leadership:Serve as a technical sounding board for AI team members on ML architecture decisions.Mentor team members on best practices for production ML system design and implementation.Communicate complex technical concepts clearly to both technical and non-technical stakeholders.Collaborate across AI teams to ensure seamless integration.Guide strategic decisions on when to use classical ML versus generative AI approaches.Strategic Decision Making:Evaluate problems to determine optimal solutions: classical ML, GenAI, or analytical methods.Integrate generative AI tools into workflows without over-relying on them.Design ML systems that integrate seamlessly with existing architectures.Provide technical guidance on model selection, evaluation metrics, and performance optimization.Stay current with ML best practices while maintaining focus on practical solutions.



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