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I am a dynamic AI/ML and Software Engineer with 3+ years of experience architecting scalable machine learning systems, cloud-native applications, and data pipelines in fintech, fraud detection, and regulated sectors. I specialize in supervised, unsupervised, and reinforcement learning, NLP, generative AI/LLMs, predictive modeling, and explainable AI, backed by strong software engineering foundations in Python, SQL, distributed systems, CI/CD, containerization (Docker/Kubernetes), and cloud platforms (AWS/Azure/GCP). I excel at translating business needs into robust, compliant AI strategies while thriving in agile, cross-functional teams. I am targeting roles in Machine Learning Engineering, MLOps/Platform ML Engineering, Data Science, NLP Specialization, AI Product Management, AI Research, Cloud & Infrastructure ML Engineering, Fraud Detection/Analytics Leadership, Explainable/Responsible AI, and Software Engineering.…I am a dynamic AI/ML and Software Engineer with 3+ years of experience architecting scalable machine learning systems, cloud-native applications, and data pipelines in fintech, fraud detection, and regulated sectors. I specialize in supervised, unsupervised, and reinforcement learning, NLP, generative AI/LLMs, predictive modeling, and explainable AI, backed by strong software engineering foundations in Python, SQL, distributed systems, CI/CD, containerization (Docker/Kubernetes), and cloud platforms (AWS/Azure/GCP). I excel at translating business needs into robust, compliant AI strategies while thriving in agile, cross-functional teams. I am targeting roles in Machine Learning Engineering, MLOps/Platform ML Engineering, Data Science, NLP Specialization, AI Product Management, AI Research, Cloud & Infrastructure ML Engineering, Fraud Detection/Analytics Leadership, Explainable/Responsible AI, and Software Engineering.

Yuvraj Patel

Data Scientist, AI Engineer, Full Stack Developer, +4

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I am a dynamic AI/ML and Software Engineer with 3+ years of experience architecting scalable machine learning systems, cloud-native applications, and data pipelines in fintech, fraud detection, and regulated sectors. I specialize in supervised, unsupervised, and reinforcement learning, NLP, generative AI/LLMs, predictive modeling, and explainable AI, backed by strong software engineering foundations in Python, SQL, distributed systems, CI/CD, containerization (Docker/Kubernetes), and cloud platforms (AWS/Azure/GCP). I excel at translating business needs into robust, compliant AI strategies while thriving in agile, cross-functional teams. I am targeting roles in Machine Learning Engineering, MLOps/Platform ML Engineering, Data Science, NLP Specialization, AI Product Management, AI Research, Cloud & Infrastructure ML Engineering, Fraud Detection/Analytics Leadership, Explainable/Responsible AI, and Software Engineering.…I am a dynamic AI/ML and Software Engineer with 3+ years of experience architecting scalable machine learning systems, cloud-native applications, and data pipelines in fintech, fraud detection, and regulated sectors. I specialize in supervised, unsupervised, and reinforcement learning, NLP, generative AI/LLMs, predictive modeling, and explainable AI, backed by strong software engineering foundations in Python, SQL, distributed systems, CI/CD, containerization (Docker/Kubernetes), and cloud platforms (AWS/Azure/GCP). I excel at translating business needs into robust, compliant AI strategies while thriving in agile, cross-functional teams. I am targeting roles in Machine Learning Engineering, MLOps/Platform ML Engineering, Data Science, NLP Specialization, AI Product Management, AI Research, Cloud & Infrastructure ML Engineering, Fraud Detection/Analytics Leadership, Explainable/Responsible AI, and Software Engineering.

Available to hire

I am a dynamic AI/ML and Software Engineer with 3+ years of experience architecting scalable machine learning systems, cloud-native applications, and data pipelines in fintech, fraud detection, and regulated sectors.

I specialize in supervised, unsupervised, and reinforcement learning, NLP, generative AI/LLMs, predictive modeling, and explainable AI, backed by strong software engineering foundations in Python, SQL, distributed systems, CI/CD, containerization (Docker/Kubernetes), and cloud platforms (AWS/Azure/GCP). I excel at translating business needs into robust, compliant AI strategies while thriving in agile, cross-functional teams. I am targeting roles in Machine Learning Engineering, MLOps/Platform ML Engineering, Data Science, NLP Specialization, AI Product Management, AI Research, Cloud & Infrastructure ML Engineering, Fraud Detection/Analytics Leadership, Explainable/Responsible AI, and Software Engineering.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Large Language Models

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Work Experience

Software Engineer Intern at GeoComply

May 1, 2025 - Present

Architected and implemented supervised learning fraud-detection models on geolocation/digital identity datasets using Python, scikit-learn, and XGBoost. Built scalable ETL pipelines with SQL, Pandas, and Apache Airflow to handle high-volume transaction streams. Developed SHAP-based explainable AI dashboards with Tableau to improve decision transparency and regulatory compliance. Led A/B testing and model evaluations to reduce false positives and validate performance with statistical tests. Deployed containerized ML microservices using Docker and Kubernetes on cloud infrastructure to support real-time fraud analysis and scalable production systems.

Software Engineer at Hexaware Technologies

July 1, 2023 - October 14, 2025

Built and deployed supervised learning models for customer segmentation and dynamic pricing; created NLP classification pipelines to automate document processing; developed reinforcement learning for customer lifetime value optimization. Orchestrated CI/CD-enabled AWS pipelines (Lambda, S3, SageMaker) to automate retraining and reduce operational overhead. Implemented SHAP-based interpretability and Tableau dashboards for governance in regulated banking. Performed A/B experiments for recommendations and automated feature engineering to accelerate prototyping-to-production.

Software Engineer Intern at GeoComply

May 1, 2025 - November 3, 2025

Architected and implemented supervised learning fraud-detection models using Python, scikit-learn, and XGBoost on geolocation/digital identity datasets, achieving 19% higher anomaly detection accuracy and fortifying compliance in financial/gaming industries. Developed scalable ETL data pipelines with SQL, Pandas, and Apache Airflow to handle high-volume transaction streams, slashing processing latency by 27% and enabling real-time fraud analysis for mission-critical systems. Engineered explainable AI dashboards leveraging SHAP for model interpretability and Tableau for visualization, enhancing stakeholder decision-making transparency and ensuring regulatory adherence in high-stakes environments. Led A/B testing and rigorous model evaluations for fraud-prediction algorithms, cutting false positives by 14%, optimizing operational efficiency, and validating performance metrics through statistical hypothesis testing. Designed and deployed containerized ML microservices using Docker and Kub

Software Engineer at Hexaware Technologies

July 1, 2023 - July 1, 2023

Built and deployed supervised learning models in Python and scikit-learn for customer segmentation and dynamic pricing optimization, delivering 20% uplift in campaign ROI and supporting revenue growth for financial services clients. Created NLP classification pipelines with TensorFlow and Hugging Face Transformers to automate document processing, reducing manual reviews by 35% and boosting compliance accuracy in regulated banking workflows. Developed reinforcement learning models for customer lifetime value prediction in retail banking, enabling data-driven cross-sell/upsell strategies that increased retention by 14% and enhanced product adoption. Orchestrated end-to-end ML pipelines on AWS (including Lambda, S3, and SageMaker) with automated retraining via CI/CD workflows, minimizing operational overhead by 40% and ensuring seamless model updates in production. Delivered responsible AI solutions with SHAP-based interpretability and Tableau dashboards, fostering stakeholder trust, regu