Hire Abhishek K. - MLOps Engineer

* Designed and deployed end-to-end MLOps pipelines, ensuring automation, scalability, and reproducibility. * Developed and optimized Machine Learning models for tasks such as Xgboost and Scikit Learn * Managed cloud infrastructure using Terraform and deployed models on platforms like GCP for scalable performance. * Implemented CI/CD workflows (Gitlab Actions) for automated model testing, validation, and deployment. * Developed enterprise AI solutions using Retrieval-Augmented Generation (RAG), Google Gemini, ADK and FastAPI to build intelligent search and retrieval systems, improving data accessibility and supporting better decision-making processes

* Designed and deployed end-to-end MLOps pipelines, ensuring automation, scalability, and reproducibility. * Developed and optimized Machine Learning models for tasks such as image embedding, layout detection, and enterprise search. * Managed cloud infrastructure using Terraform and deployed models on platforms like Azure for scalable performance. * Implemented CI/CD workflows (GitHub Actions) for automated model testing, validation, and deployment. * Ensured secure deployments by integrating secret management tools like Azure Key Vault. * Developed enterprise AI solutions using Retrieval-Augmented Generation (RAG), OpenAI, and FastAPI to build intelligent search and * retrieval systems, improving data accessibility and supporting better decision-making processes * Deployed TensorFlow/PyTorch models using Azure ML and GitLab CI/CD, streamlining the model deployment process and ensuring * efficient integration into production environments

* During my tenure, I successfully managed technical escalations from valued clients and efficiently developed custom applications tailored to meet their specific requirements. One of my key projects involved collaborating with Wipro on the Internal Workforce Optimization Application. As part of this project, I took charge of deploying essential reports such as Accuracy Report, Skill Trend Report, and Hype Chart, ensuring accurate and timely insights for decision-making. * Furthermore, I demonstrated my expertise in software development by crafting REST APIs for Machine Learning models and Web Applications using Python Django REST Framework (DRF), Flask, and Elasticsearch. In addition, I contributed to the advancement of asynchronous APIs by utilizing RabbitMQ and ZeroMQ, further enhancing the application's performance and responsiveness. * Orchestrated the deployment of crucial reports such as AccuracyReport, SkillTrend Report, and Hype Chart, offering precise and timely insights for strategic decision-making * Successfully migrated the Legacy IWO application from PHP to Python (utilizing Fast API and RMQ), significantly * reducing ingestion errors to an impressive 0.01% . * Lead feature development within the Product team, ensuring adherence to project requirements and quality * benchmarks. * Conduct thorough testing and deploy features via Jenkins-managed Docker containers to Client Azure VMs, * enhancing product delivery efficiency and user experience. * Collaborated with DevOps team to architect and deploy the application across various microservices and * applications. * Implemented load balancer strategies to efficiently manage high traffic, resulting in reduced server load. * Leveraged Docker, Kubernetes, Nginx, RMQ, and Elasticsearch for streamlined deployment and enhanced scalability.