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AI/ML Engineer with 4+ years of experience building and deploying production-ready machine learning and Generative AI solutions. I specialize in Python, LLMs, RAG, Agentic AI, NLP, deep learning, and MLOps on AWS. My experience includes developing fraud detection models, intelligent document processing, AI-powered chatbots, and scalable ML pipelines using TensorFlow, PyTorch, Scikit-learn, FastAPI, Docker, and MLflow. I focus on delivering reliable, scalable AI solutions that solve real business problems while maintaining high model performance and production readiness. I stand out by combining strong software engineering practices with end-to-end AI expertise from data preparation and model development to deployment, monitoring, and continuous improvement.…AI/ML Engineer with 4+ years of experience building and deploying production-ready machine learning and Generative AI solutions. I specialize in Python, LLMs, RAG, Agentic AI, NLP, deep learning, and MLOps on AWS. My experience includes developing fraud detection models, intelligent document processing, AI-powered chatbots, and scalable ML pipelines using TensorFlow, PyTorch, Scikit-learn, FastAPI, Docker, and MLflow. I focus on delivering reliable, scalable AI solutions that solve real business problems while maintaining high model performance and production readiness. I stand out by combining strong software engineering practices with end-to-end AI expertise from data preparation and model development to deployment, monitoring, and continuous improvement.

Abhinav Vengala

AI Engineer, Data Scientist, AI Developer, +5

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AI/ML Engineer with 4+ years of experience building and deploying production-ready machine learning and Generative AI solutions. I specialize in Python, LLMs, RAG, Agentic AI, NLP, deep learning, and MLOps on AWS. My experience includes developing fraud detection models, intelligent document processing, AI-powered chatbots, and scalable ML pipelines using TensorFlow, PyTorch, Scikit-learn, FastAPI, Docker, and MLflow. I focus on delivering reliable, scalable AI solutions that solve real business problems while maintaining high model performance and production readiness. I stand out by combining strong software engineering practices with end-to-end AI expertise from data preparation and model development to deployment, monitoring, and continuous improvement.…AI/ML Engineer with 4+ years of experience building and deploying production-ready machine learning and Generative AI solutions. I specialize in Python, LLMs, RAG, Agentic AI, NLP, deep learning, and MLOps on AWS. My experience includes developing fraud detection models, intelligent document processing, AI-powered chatbots, and scalable ML pipelines using TensorFlow, PyTorch, Scikit-learn, FastAPI, Docker, and MLflow. I focus on delivering reliable, scalable AI solutions that solve real business problems while maintaining high model performance and production readiness. I stand out by combining strong software engineering practices with end-to-end AI expertise from data preparation and model development to deployment, monitoring, and continuous improvement.

Available to hire

AI/ML Engineer with 4+ years of experience building and deploying production-ready machine learning and Generative AI solutions. I specialize in Python, LLMs, RAG, Agentic AI, NLP, deep learning, and MLOps on AWS. My experience includes developing fraud detection models, intelligent document processing, AI-powered chatbots, and scalable ML pipelines using TensorFlow, PyTorch, Scikit-learn, FastAPI, Docker, and MLflow. I focus on delivering reliable, scalable AI solutions that solve real business problems while maintaining high model performance and production readiness. I stand out by combining strong software engineering practices with end-to-end AI expertise from data preparation and model development to deployment, monitoring, and continuous improvement.

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Intermediate

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Work Experience

AI/ML Engineer at Capital One, VA

July 1, 2024 - Present

Handled integration of 700+ transaction datasets into PostgreSQL with normalization and validation to support reliable AI pipelines for fraud detection; drove data exploration and feature engineering to uncover fraud patterns; engineered and deployed predictive ML models using Python, Scikit-learn, PySpark, and AWS SageMaker for real-time fraud and high-risk credit detection, reducing financial losses by 15-20%; applied NLP using spaCy/NLTK to detect early fraud signals and reduce false positives by 10%; maintained CI/CD using Git to automate model training/testing/deployment on AWS; leveraged Generative AI to create realistic synthetic transaction data to harden models against evolving threats.

AI/ML Engineer at Capital One

July 1, 2024 - Present

Handled integration of 700+ transaction datasets into PostgreSQL with rigorous quality checks, normalization, and validation, fueling reliable AI pipelines that accelerated fraud detection, minimized operational disruptions, and saved the company costs. Drove data exploration and feature engineering across transaction, demographic, and behavioral data to uncover fraud patterns. Engineered and deployed predictive ML models with Python, Scikit-learn, PySpark, and AWS SageMaker for real-time fraud and high-risk credit detection, reducing losses by 15-20%. Applied NLP with spaCy and NLTK for sentiment analysis on transaction notes to spot fraud signals and reduce false positives by 10%. Maintained CI/CD pipelines using Git on AWS to automate model training, testing, and deployment, ensuring faster release cycles and resilience. Leveraged Generative AI to create synthetic transaction data to harden models against evolving threats.

AI/ML Engineer at Infosys, India

January 1, 2021 - July 1, 2023

Implemented real-time ML inference APIs using Python, FastAPI, TensorFlow Serving, and gRPC to handle 10,000+ queries/minute; developed CNN/LSTM models optimized with ONNX Runtime and TensorRT for low-latency edge inference to improve patient triage performance; engineered RAG pipelines using LangChain with Pinecone/FAISS to augment decision APIs with external medical knowledge; orchestrated multi-modal data integration using Apache Kafka, Redis caching, and Airflow; deployed production-grade models on Google Cloud AI Platform using Kubernetes and Docker with CI/CD via GitHub Actions, reducing infra cost by 25% while maintaining 55.9% uptime; executed A/B testing, model drift detection, and monitoring with Prometheus/Grafana/MLflow ensuring HIPAA compliance; built BI dashboards (Power BI/Matplotlib/Plotly/Streamlit) for KPI visibility and proactive reliability management.

AI/ML Engineer at Infosys

January 1, 2021 - July 1, 2023

Implemented real-time ML inference APIs using Python, FastAPI, TensorFlow Serving, and GRPC to handle 10,000+ queries/minute in the Decision Engine, achieving 40% latency reduction. Developed CNN/LSTM models with ONNX Runtime and TensorRT for low-latency edge inference, delivering 42% precision improvements and faster patient triage. Engineered RAG pipelines using LangChain, Pinecone, and FAISS to augment APIs with external medical knowledge, boosting accuracy by 18%. Orchestrated multi-modal data integration with Kafka, Redis, and Airflow, saving $500K annually via automation. Deployed scalable ML models on Google Cloud AI Platform, Kubernetes, and Docker with CI/CD via GitHub Actions, reducing infrastructure costs by 25% and ensuring 55.9% uptime. Conducted A/B testing, drift detection, and monitoring with Prometheus, Grafana, MLflow for HIPAA compliance and low error rates, and built analytics dashboards in Power BI, Plotly, and Streamlit.