Sivaprasad

Highly accomplished AI Product Development Manager and AI Research, AI Agent, Data Scientist, and Full Stack AI Developer with over 6+ years of experience in Generative AI, machine learning, cloud computing, and AI-powered automation across e-commerce, healthcare, finance, and technology industries. Proven expertise in designing, deploying, and maintaining scalable ML infrastructure for MLOps workflows, predictive analytics, and intelligent automation solutions using GCP, AWS, Azure, and advanced Generative AI models.

Microsoft Power

Apps and Dynamics 365 streamline business operations by enabling custom app development and seamless data integration. Their automation capabilities and AI-driven insights enhance efficiency and decision-making.

AI Research & AI Product Development Manager | Data Scientist - JobsHorn - United Kingdom (Remote)

(2024-03 - 2025-10)

• Led development of Generative AI models for workflow automation, predictive analytics, and NLP applications across industries.
• Integrated LLMs into MLOps workflows, utilizing Retrieval-Augmented Generation (RAG) to enhance AI solutions.
• Designed and deployed AI-powered APIs using FastAPI, Flask, Docker, and Kubernetes, integrating LLMs into scalable systems on Azure and GCP.
• Developed predictive models for healthcare, patient analytics, and business intelligence, ensuring optimized decision-making.
• Implemented fine-tuning strategies (SFT, LoRA) for AI customization using Hugging Face, PyTorch, and TensorFlow.
• Developed AI-powered virtual assistants with natural language processing (NLP) to enhance patient interactions.
• Automated AI-driven medical insights, deploying Vertex AI, Kubeflow Pipelines, ensuring compliance with HIPAA and security protocols.
• Built IoT-driven analytics for cold storage health monitoring, utilizing BigQuery, Apache Airflow, and machine learning forecasts.
• Developed deep learning models using PyTorch and TensorFlow, optimizing predictive healthcare analytics.
• Built enterprise RAG and knowledge retrieval systems using LlamaIndex — document indexing, multi-document agents, sub-question query engines, and custom ingestion pipelines integrated with Qdrant and ChromaDB vector databases.
• Integrated OpenAI GPT models (GPT-4, GPT-4o, GPT-3.5-turbo) and open-source LLMs (Mistral, LLaMA, Phi-3, Gemma) into document processing and conversational AI pipelines, selecting models based on accuracy, latency, and cost.
• Implemented data drift and concept drift monitoring pipelines using Evidently AI and Arize Phoenix — detecting feature distribution shifts (PSI, KS-test) and triggering automated model retraining when performance thresholds were breached.
• Applied ML models (Regression, Random Forest, CatBoost, XGBoost, Decision Tree) for classification and prediction tasks; evaluated using Confusion Matrix, Precision, Recall, F1-Score, and ROC-AUC.
• Built full-stack AI-powered applications with JavaScript, HTML5, CSS3, and Tailwind CSS frontends connected to FastAPI/Flask backends, with PostgreSQL as the primary relational data store.
• Acted as liaison between technical AI teams and non-technical business stakeholders — translating model outcomes into clear business language, presenting AI strategy to senior leadership, and converting business requirements into engineering specifications.

Data Scientist - JobsHorn - Atlanta, GA, USA

(2020-01 - 2023-12)

• Built AI-driven data warehouses using Apache Nifi, Hadoop, integrating structured and unstructured business data from healthcare, finance, and e-commerce.
• Developed predictive models for disease risk analysis, patient readmission rates, and healthcare optimization.
• Deployed OpenAI's machine learning models for patient analytics and personalized treatment planning at Kaiser.
• Designed doctor performance analytics using Apache Kafka, Tableau, and Hadoop/Spark for real-time insights.
• Developed NLP solutions for sentiment analysis and customer feedback tracking, improving business intelligence and AI automation.
• Optimized appointment scheduling with A/B testing via Databricks, ensuring seamless patient experience.
• Applied deep learning architectures with PyTorch and TensorFlow to enhance predictive healthcare models.
• Integrated AI-powered chatbots utilizing LLMs and NLP, ensuring accurate and personalized healthcare responses.
• Automated machine learning workflows with Kubeflow Pipelines, ensuring scalability and reproducibility in AI research.

Lead Talent Acquisition Specialist | AI-Powered Tech Recruiter - SohanIT Inc - Remote

(2018-09 - 2019-11)

• Managed end-to-end AI-driven recruitment strategies, leveraging Generative AI tools for automated candidate sourcing, matching, and onboarding.
• Implemented AI-based candidate matching, optimizing talent acquisition processes and improving hire quality.
• Utilized AI-driven sourcing platforms like LinkedIn Recruiter, AI-powered ATS, ensuring diversity, fairness, and transparency in recruitment.
• Developed AI models for workforce analytics, improving hiring efficiency and recruitment process automation.

Master's - AI Management - Swansea University (2025)

B.Tech - Electrical & Electronics Engineering - JNTUA College of Engineering (2015)