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I am an AI/ML Engineer with 4+ years of experience delivering enterprise solutions in predictive analytics, deep learning, and generative AI. I have enhanced and deployed ML models that improved forecasting accuracy, optimized performance, and reduced operational costs. I am skilled at translating complex models into actionable business insights, ensuring Responsible AI, bias mitigation, and privacy compliance, and driving measurable outcomes across global industries. I complement technical expertise with problem-solving and collaboration to achieve business impact.…I am an AI/ML Engineer with 4+ years of experience delivering enterprise solutions in predictive analytics, deep learning, and generative AI. I have enhanced and deployed ML models that improved forecasting accuracy, optimized performance, and reduced operational costs. I am skilled at translating complex models into actionable business insights, ensuring Responsible AI, bias mitigation, and privacy compliance, and driving measurable outcomes across global industries. I complement technical expertise with problem-solving and collaboration to achieve business impact.

Himabindu Voruganti

AI Engineer, Data Scientist, Full Stack Developer, +2

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I am an AI/ML Engineer with 4+ years of experience delivering enterprise solutions in predictive analytics, deep learning, and generative AI. I have enhanced and deployed ML models that improved forecasting accuracy, optimized performance, and reduced operational costs. I am skilled at translating complex models into actionable business insights, ensuring Responsible AI, bias mitigation, and privacy compliance, and driving measurable outcomes across global industries. I complement technical expertise with problem-solving and collaboration to achieve business impact.…I am an AI/ML Engineer with 4+ years of experience delivering enterprise solutions in predictive analytics, deep learning, and generative AI. I have enhanced and deployed ML models that improved forecasting accuracy, optimized performance, and reduced operational costs. I am skilled at translating complex models into actionable business insights, ensuring Responsible AI, bias mitigation, and privacy compliance, and driving measurable outcomes across global industries. I complement technical expertise with problem-solving and collaboration to achieve business impact.

Available to hire

I am an AI/ML Engineer with 4+ years of experience delivering enterprise solutions in predictive analytics, deep learning, and generative AI. I have enhanced and deployed ML models that improved forecasting accuracy, optimized performance, and reduced operational costs.

I am skilled at translating complex models into actionable business insights, ensuring Responsible AI, bias mitigation, and privacy compliance, and driving measurable outcomes across global industries. I complement technical expertise with problem-solving and collaboration to achieve business impact.

Skills

Experience Level

Expert

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Expert

Language

English

Fluent

Work Experience

AI Engineer at Capital One Financial

January 1, 2024 - Present

Led development of a GPT-4–based document analysis workflow, reducing manual review time by 32% while maintaining accuracy standards required for regulated financial reporting and audit readiness. Designed retrieval-augmented generation pipelines using embeddings and vector databases, improving internal search answer relevance by 27% and minimizing incorrect responses caused by incomplete or outdated source information. Refined prompt logic and response validation rules, lowering reprocessing requests by 22% and improving consistency of AI outputs used by risk and compliance analysts during decision reviews. Deployed FastAPI inference services on AWS, supporting thousands of monthly requests with stable latency under peak usage and secure integration with existing internal platforms. Introduced model monitoring and drift checks, identifying data quality issues early and preventing performance degradation across multiple production releases. Partnered with product and security teams t

AI Engineer at Mphasis

January 1, 2021 - December 1, 2022

Developed NLP models for document classification and entity extraction, improving automated data capture accuracy by 18% and reducing manual correction effort for downstream business teams. Built semantic search functionality using embeddings, cutting document lookup time by 40% for users working with large unstructured knowledge repositories. Designed preprocessing pipelines for structured and unstructured datasets, improving model training reliability and reducing data-related inference failures. Integrated machine learning models through REST APIs, enabling batch and near-real-time predictions consumed by multiple internal applications. Evaluated model performance using validation metrics and stakeholder feedback, iterating on features to improve usability and adoption across client-facing systems. Collaborated within Agile teams using Git-based workflows, delivering tested AI features on schedule while coordinating with data, QA, and application teams.

AI/ML Engineer at Cisco

January 1, 2024 - Present

Engineered predictive ML algorithms using Python and XGBoost, improving network traffic forecasting accuracy by 28%, enabling proactive bandwidth allocation and optimizing enterprise network efficiency. Developed deep learning pipelines with PyTorch and TensorFlow, reducing false positive alerts by 22% and strengthening real-time security monitoring across large-scale enterprise systems. Automated model training, validation, and deployment pipelines using Docker and CI/CD frameworks, reducing deployment timelines by 40% and accelerating enterprise AI solution delivery. Executed end-to-end data preprocessing and feature engineering across multi-source datasets, achieving 99% data integrity and enhancing predictive model reliability and operational performance. Collaborated with cross-functional teams to translate analytical outputs into operational strategies, optimizing IT resource utilization and supporting data-driven decision making across global operations. Monitored and retrained

AI/ML Engineer at Mphasis

January 1, 2021 - December 1, 2022

Designed regression and classification ML models, improving supply chain forecasting accuracy by 35%, reducing stockouts, operational delays, and enhancing overall logistics efficiency for clients. Applied clustering and segmentation techniques for customer behavior analytics, increasing marketing campaign effectiveness by 18% and boosting client engagement and ROI. Built end-to-end ML pipelines with Python, Scikit-learn, and Flask, enabling real-time insights and accelerating data-driven decision-making for enterprise applications. Performed advanced data wrangling, cleaning, and feature engineering on structured and unstructured datasets, reducing missing data errors by 25% and improving model reliability. Monitored post-deployment model performance, recalibrating algorithms to maintain 3% deviation in accuracy, ensuring consistent predictions for enterprise-level business decisions. Partnered with product and business teams to operationalize ML insights into actionable strategies, d