Senior AI Model Developer

2 weeks ago

shimoga, India beBeeMachineLearning Full time

Job TitleA highly skilled Machine Learning Engineer is needed to design and implement cutting-edge ML pipelines for recommendation systems, search ranking, and classification problems.The ideal candidate will have expertise in designing and implementing end-to-end ML pipelines for complex business applications.We are seeking a talented individual with experience in building and optimizing traditional ML models using techniques such as ensemble methods, SVMs, gradient boosting, and neural networks.This role requires a professional who can develop time series forecasting models and ranking algorithms for complex business applications.The Machine Learning Engineer will also be responsible for implementing feature engineering pipelines that handle real-world data noise and edge cases.A strong background in creating robust data preprocessing and validation systems that ensure model reliability in production is essential.Key ResponsibilitiesThe Machine Learning Engineer will be responsible for:Deploying ML models using Docker containerization and REST API frameworks (Flask/FastAPI).Implementing model serving solutions on Azure Container Instances with proper monitoring and alerting.Building MLOps pipelines using MLflow for experiment tracking and model registry management.Designing scalable data workflows using Apache Airflow and Azure Data Factory for ETL operations.Establishing model versioning, rollback strategies, and performance monitoring in production environments.About the RoleThis is an exciting opportunity for a talented Machine Learning Engineer to join our team and contribute to the development of innovative ML solutions.Serving as a technical sounding board for AI team members on ML architecture and approach decisions.Mentoring team members on best practices for production ML system design and implementation.Communicating complex technical concepts clearly to both technical and non-technical stakeholders.Collaborating across AI, web development, and system architecture teams to ensure seamless integration.Guiding strategic decisions on when to use traditional ML versus generative AI approaches.RequirementsTo be successful in this role, you will need:Evaluate problems to determine optimal solutions: classical ML, GenAI, or simpler analytical methods.Integrate generative AI tools effectively into workflows without over-relying on them.Design ML systems that integrate seamlessly with existing web application architectures.Provide technical guidance on model selection, evaluation metrics, and performance optimization.Stay current with ML best practices while maintaining focus on practical, business-driven solutions.

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