Principal Software Developer specializing in Machine Learning Infrastructure, Salesforce core products, and Mobile Banking Solutions. From requirement gathering to software delivery, my expertise encompasses design, architecture, solution development, testing, product support, and documentation. Machine Learning Expertise: Built a robust Salesforce Machine Learning platform, delivering billions of predictions daily. Proud owner of key microservices like Modelstore and MLConfig. SaaS & Enterprise Solutions: Designed, developed, and provided solutions for SaaS Enterprise software and Financial Institutions, emphasizing quality, scalability, and security. Salesforce Cloud Solutions: Developed products on the Salesforce platform, ensuring multi-tenancy, security, scalability, and high performance. Service Ownership: Embraced a full-service ownership model, including Service Reliability (SLA/SLO/SLI), comprehensive documentation, and on-call support. Salesforce AI Platform: Powering GenAI and traditional AI use cases, from Salesforce AI Research to Einstein GPT and beyond. The platform serves various AI needs across Sales, Service, Marketing, and Mulesoft organizations. AI Tech Stack: Features cutting-edge GenAI technologies, including OpenAI, Huggingface, and Cohere, complemented by open-source systems like Nvidia Triton. It also integrates cloud solutions such as AWS Sagemaker. This platform is versatile, supporting custom application development across major AI frameworks like TensorFlow, Keras, PyTorch, and Scikit-learn. Specialized AI Components: - Multi-tenant ML model training, evaluation, and publishing. - Real-time, in-memory Complex ML Graph Serving layer. - Hyperparameter tuning and AutoML. - B2C scale online and offline inference, handling 100k requests/sec with minimal latency. Tech Stack: Java, Python, Scala, JavaScript, Oracle, Postgres, AWS SageMaker, Terraform, Solr, Elastic Search, Git, Maven, k8s, Helm, Databricks, Sumologic, Splunk, Docker, Jenkins, Swagger, JMeter, Kafka, and more.