# Katipalli Manisha > AI/ML Engineer | Generative AI (LLMs, RAG) | Real-Time ML Systems | MLOps | AWS Profile: https://flows.cv/katipalli AI/ML Engineer with 4+ years of experience building scalable, production-grade machine learning and Generative AI (GenAI) solutions across finance, technology, and research domains. Expertise in Transformers, CNNs, RNNs, LLMs, Hugging Face, and advanced feature engineering. Strong experience in MLOps, CI/CD, Docker, Kubernetes, MLflow/Kubeflow, and cloud-native deployment (AWS SageMaker, Azure ML). Skilled in real-time and batch data pipelines (Kafka, Spark, Airflow, AWS Glue), model monitoring, drift detection, LLMOps, prompt engineering, and cost-optimized inference. Proven ability to deliver high-impact ML and GenAI solutions aligned with business objectives. ## Work Experience ### Senior Machine Learning Engineer @ JPMorganChase Jan 2024 | United States Designed and deployed production-grade ML models for fraud detection and recommendation systems using Python, TensorFlow, and XGBoost, improving model accuracy by 40% and reducing prediction latency by 50%. • Architected real-time streaming pipelines using Apache Kafka, AWS Glue, and PySpark to process 2M+ daily transactions for near real-time risk scoring and feature generation. • Implemented scalable feature engineering pipelines, including feature extraction, hashing, normalization, and time-windowing, ensuring consistency across batch and streaming systems. • Built and automated end-to-end MLOps pipelines using AWS SageMaker, MLflow, and CI/CD (GitLab), reducing deployment time by 45% and enabling continuous training and delivery. • Containerized model serving using Docker and deployed RESTful APIs (FastAPI/Flask) on Kubernetes and AWS ECS with autoscaling and lowlatency inference. • Developed and integrated model monitoring, logging, and data drift detection using SageMaker Model Monitor, Evidently AI, and Prometheus, improving issue detection by 30%. • Reducedfraud-related false positives by 25% through ensemble modeling, threshold optimization, and continuous A/B testing. • Applied transformer-based NLP models (BERT) and embedding techniques (Word2Vec, sentence-transformers) to financial text, improving recommendation relevance by 35% and user engagement by 45%. • Developed GenAI-powered solutions leveraging LLMs, prompt engineering, and retrieval-augmented generation (RAG) for intelligent document processing and contextual recommendations. • Conducted rigorous model evaluation using cross-validation, ablation studies, and metrics such as ROC-AUC, precision, recall, F1-score, and RMSE to ensure robustness. • ### AI/ML Engineer @ Tata Consultancy Services Jan 2020 – Jan 2023 | India negatives. • Built scalable data preprocessing and feature engineering pipelines using Spark and Pandas, including sliding windows and behavioral embeddings. • DevelopedRESTful microservices for model inference using AWS Lambda and FastAPI/Flask, ensuring scalable and reliable deployment. • Implemented CI/CD pipelines using Jenkins and GitLab CI for automated model testing, validation, deployment, and rollback strategies. • Built recommendation systems (collaborative and content-based), increasing user engagement by 35% and product usage by 20%. • Optimized inference performance by 50% through batching, model quantization, and asynchronous processing. • Integrated feature stores, Redis caching, and autoscaling mechanisms to improve throughput and system scalability. • Conducted model validation using cross-validation, ROC-AUC/PR curves, and confusion matrix-based threshold tuning, followed by A/B testing. • Contributed to early-stage NLP and LLM-based solutions, including text embeddings, semantic search, and prompt-based workflows for automation use cases. • Mentored junior team members, led code reviews, and documented SOPs and production troubleshooting guides. ## Education ### Master's degree Texas A&M University-Kingsville ### Bachelor of Technology - BTech R.V.R. & J.C. College of Engineering ## Contact & Social - LinkedIn: https://linkedin.com/in/katipallimanisha - Email: mailto:kmanisha1298@gmail.com --- Source: https://flows.cv/katipalli JSON Resume: https://flows.cv/katipalli/resume.json Last updated: 2026-04-16