Dev

About Dev

Inspired Developer with broad expertise in the IT industry and developing web and mobile applications and being involved in Back-end Development areas with Proficiency in developing APIs and Performing testing- Experience in working with object-oriented programming, events, and cookies operations in order to build interactive web pages- Familiarity with development best practices such as code reviews, unit testing, integration testing, and user acceptance testing (UAT)- Strong Expertise in MySQL, PostgreSQL, and NO-SQL databases like MongoDB and Couch DB- Complete understanding of Software Development Lifecycle and Core area of experience in validating end-to-end business scenarios of B2B (Business to Business) applications, Enterprise Applications- Experience with continuous integration and automation using JENKINS & Used JIRA for tracking and Updating Project issue- Expertise in full life cycle application development and also good experience in Unit testing and Test-Driven Development (TDD) and Behaviour driven Development.

Experience

1. Senior Ml Engineer

   S&P Global

   Oct 2022 — Present

   Designed state-of-the-art machine learning models, including neural networks, GANs, and Large Language Models (LLMs), to enhance generative AI system capabilities, facilitating natural language understanding and generation tasks.Leveraged TensorFlow and PyTorch for developing and fine-tuning deep learning models, improving the accuracy and performance of predictive analytics.Employed BERT and GPT-3 models for natural language processing tasks, enhancing the system\'s ability to understand and generate human-like text. Implemented reinforcement learning techniques to optimize decision-making processes in credit risk and fraud detection scenarios.Integrated advanced AI and ML frameworks like Hugging Face Transformers and OpenAI\'s GPT-4 for building robust generative AI applications.Used cloud-based ML services such as AWS SageMaker and Google AI Platform for scalable model training and deployment, ensuring high availability and performance.Applied transfer learning techniques to leverage pre-trained models for specific use cases, reducing training time and improving model accuracy. Conducted extensive hyperparameter tuning and model evaluation using tools like Optuna and Hyperopt to maximize the performance of machine learning models.Developed real-time data processing pipelines using Apache Kafka and Apache Flink, enabling the system to handle high-velocity data streams for fraud detection. Utilized Docker and Kubernetes for containerizing and orchestrating ML models, ensuring consistent deployment across various environments.Integrated with data visualization tools like Tableau and Power BI to present insights and model predictions in an accessible and actionable format. Developed the blueprint for a Datalake in S3 containing insurance customers’ data with billions of curated and filtered records in parquet. Developed ETL pipelines, data filtering pipeline in PySpark & EMR for an R&D project for ISO’s data governance team for their major insurance carriers.