Rahul  ·  Senior ML / MLOps Engineer  ·  8+ yrs

Overview: Developed an AI-powered EdTech platform that provides real-time feedback to users on their presentation skills using speech and facial recognition. Responsibilities: Implemented AI models for real-time speech and facial recognition, using AWS AI services for instant user feedback. Leveraged Databricks for processing live video and audio data and applying AI models to evaluate user performance. Deployed and monitored AI models for real-time evaluation, using MLOps frameworks to ensure continuous updates and retraining.

Overview: Developed an AI-based SaaS application for online eye health, incorporating features for online eye tests, PD distance measurement, and lensometer functionality. Responsibilities: Developed and integrated AI models for online refraction and PD measurement, optimizing real-time analysis using Databricks. Designed the digital lensometer feature architecture, utilizing FastAPI to connect the front end with AWS SageMaker for accurate lens data processing. Developed automated CI/CD pipelines using Jenkins and Kubernetes to ensure seamless deployment on AWS EKS. Utilized AWS Lambda and S3 for secure processing and storage of patient data. Managed the SaaS platform's scalability by optimizing Kubernetes clusters on AWS EKS.

Overview: Developed a document query chatbot with interactive NLP features capable of understanding and extracting information from uploaded documents in real-time. Responsibilities: Integrated natural language processing models for document query interactions. Utilized Databricks for NLP model training and real-time response optimization. Built the document ingestion and query system using AWS Lambda and ECS, ensuring low-latency responses via optimized FastAPI endpoints. Set up automated pipelines for NLP model deployment using MLOps practices and Kubernetes.

Overview: Developed the backend infrastructure for a quiz system that included user management, real-time quiz assessments, and AI-powered scoring features. Responsibilities: Implemented AI algorithms to automatically score quizzes based on correct answers and subjective content, using Databricks for model training and prediction. Designed real-time quiz functionalities enabling simultaneous participation and immediate scoring using FastAPI and AWS Lambda. Built CI/CD pipelines using MLOps practices to ensure continuous retraining and updating of AI models.