Contribute to unified AI/ML capabilities by integrating classical ML models with Generative AI platforms (primarily AWS Bedrock) for applications in semiconductor manufacturing and risk analytics.
Design, build, and maintain end-to-end machine learning pipelines on Databricks, covering data preparation, feature engineering, model training, evaluation, and deployment.
Oversee daily buffet service operations across breakfast, lunch, and dinner periods, ensuring consistent food quality, presentation, and service standards
Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
MLOps/AIOps Platform Engineering: Design and implement reusable platform components and golden paths for experiment tracking, model registry, pipeline orchestration, deployment, monitoring, feedback and retraining using Databricks, MLflow and approved AWS services.
Provide technical leadership in the design, development, and deployment of production-grade AI and machine learning solutions, with a focus on geospatial applications.