Sandeep Manam

About Sandeep Manam

I\'m an AI/ML Engineer and Data Analyst with over 10 years of experience in delivering data-driven solutions across industries like e-commerce, finance, and technology. I specialize in developing and deploying machine learning models, predictive analytics, and NLP solutions, with hands-on experience in cloud platforms such as AWS and Azure. I built end-to-end machine learning pipelines, from data extraction to model deployment, utilizing advanced tools like Apache Airflow, Kafka, and Spark.Over the years, I’ve developed and deployed recommendation systems, sentiment analysis models, and various predictive solutions that have had a measurable business impact.With expertise in statistical modeling, data visualization (Tableau, Python, R), and big data technologies, I drive impactful insights and optimize business decisions. I have hands-on experience with containerization (Docker, Kubernetes), and CI/CD pipelines, ensuring seamless deployments and operational efficiency. I thrive in collaborative environments, working closely with cross-functional teams to translate data into actionable insights that optimize business performance. I’m excited about leveraging AI/ML to solve complex challenges and drive innovation.

Experience

1. Gen Ai Architect

   MasterControl

   Feb 2023 — Present · UT, US

   Developed a PDF-enhanced chatbot with asynchronous PDF processing, dynamic prompt selection, and memory management for enhanced user experience. Engineered a database chatbot integrating FAISS and SQL for efficient similarity searches and query optimization. Delivered a scalable meeting transcription system combining WhisperX, Pyannote, BART-large, and Llama3, deployed on AWS EC2 with FastAPI and RabbitMQ for real-time processing. With hands-on experience in custom dataset preparation, pipeline enhancement, and model testing for identity card fraud detection. Developed custom functions to detect and crop Malaysian identity card areas from images, improving pixel quality and accuracy. Enhanced image preprocessing pipelines for varying image sizes, ensuring model compatibility. Conducted comprehensive testing and evaluation of detection models, analyzing performance metrics including TP, FP, TN, and FN. Delivered professional documentation detailing methodologies, performance metrics, and results aligning with business requirements. Achieved a notable increase in model accuracy from 91% to 94%, contributing to enhanced security measures through improved fraud detection reliability. Experienced with a background in API development, system enhancement, and deployment automation. Developed RESTful APIs using Spring Boot, with expertise in error handling, input validation, and security implementation. Skilled in bug assessment, issue resolution, and API optimization based on performance metrics and stakeholder feedback. Hands-on experience in automating deployments using Jenkins and GitLab CI/CD pipelines, as well as implementing automated testing with Postman and JUnit for API validation. Experienced in Kubernetes for container orchestration, ensuring scalable and reliable deployments. Experienced in SQL query optimization to enhance performance and resource efficiency.

Education

• Rivier University

  Masters, Computer Information Systems