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Innovative Machine Learning Engineer with 3+ years of experience designing, deploying, and scaling production-grade ML systems and AI-driven solutions across the full ML lifecycle. Skilled in end-to-end model development, evaluation, deployment, and monitoring with strong MLOps practices. Experienced building NLP and Generative AI applications including RAG architectures and LangChain/LangGraph workflows, with proven impact on deployment speed, model accuracy, and operational reliability. Certified in Azure AI Fundamentals and AWS Machine Learning Engineer (Associate), with hands-on experience on AWS and Azure.…Innovative Machine Learning Engineer with 3+ years of experience designing, deploying, and scaling production-grade ML systems and AI-driven solutions across the full ML lifecycle. Skilled in end-to-end model development, evaluation, deployment, and monitoring with strong MLOps practices. Experienced building NLP and Generative AI applications including RAG architectures and LangChain/LangGraph workflows, with proven impact on deployment speed, model accuracy, and operational reliability. Certified in Azure AI Fundamentals and AWS Machine Learning Engineer (Associate), with hands-on experience on AWS and Azure.

Paras Godhani

AI Engineer, Data Scientist, Data Engineer, +3

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Innovative Machine Learning Engineer with 3+ years of experience designing, deploying, and scaling production-grade ML systems and AI-driven solutions across the full ML lifecycle. Skilled in end-to-end model development, evaluation, deployment, and monitoring with strong MLOps practices. Experienced building NLP and Generative AI applications including RAG architectures and LangChain/LangGraph workflows, with proven impact on deployment speed, model accuracy, and operational reliability. Certified in Azure AI Fundamentals and AWS Machine Learning Engineer (Associate), with hands-on experience on AWS and Azure.…Innovative Machine Learning Engineer with 3+ years of experience designing, deploying, and scaling production-grade ML systems and AI-driven solutions across the full ML lifecycle. Skilled in end-to-end model development, evaluation, deployment, and monitoring with strong MLOps practices. Experienced building NLP and Generative AI applications including RAG architectures and LangChain/LangGraph workflows, with proven impact on deployment speed, model accuracy, and operational reliability. Certified in Azure AI Fundamentals and AWS Machine Learning Engineer (Associate), with hands-on experience on AWS and Azure.

Available to hire

Innovative Machine Learning Engineer with 3+ years of experience designing, deploying, and scaling production-grade ML systems and AI-driven solutions across the full ML lifecycle. Skilled in end-to-end model development, evaluation, deployment, and monitoring with strong MLOps practices.

Experienced building NLP and Generative AI applications including RAG architectures and LangChain/LangGraph workflows, with proven impact on deployment speed, model accuracy, and operational reliability. Certified in Azure AI Fundamentals and AWS Machine Learning Engineer (Associate), with hands-on experience on AWS and Azure.

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Work Experience

AI & Machine Learning Engineer at Realiq

May 1, 2025 - Present

Architected and deployed end-to-end ML pipelines on AWS SageMaker and Azure ML for classification, regression, and NLP models, reducing model deployment time by 50%. Built production Generative AI applications using LangChain and LangGraph with RAG, integrating OpenAI GPT models and FAISS vector stores for document Q&A and knowledge retrieval. Implemented MLOps workflows with MLflow for experiment tracking, model versioning, and registry to ensure reproducibility and governance. Developed CI/CD pipelines using GitHub Actions and Docker for automated retraining and containerized deployment, reducing manual release effort by 65% and enabling zero-downtime deployments. Built feature engineering pipelines with PySpark/Pandas for large-scale processing, improving data preparation time by 40%. Deployed inference APIs using FastAPI and Docker, achieving sub-100ms latency with autoscaling on AWS Lambda/Azure Functions. Added monitoring for data/concept drift and performance degradation to enab

Data Analyst at Upfroz Infotech

April 1, 2023 - March 31, 2024

Performed advanced EDA on large transactional datasets using Python and SQL, identifying patterns and anomalies to guide feature selection and modeling. Built predictive models using regression analysis and time series forecasting to improve pricing strategies and demand forecasting accuracy by 30%. Created interactive Tableau dashboards for real-time KPI reporting, reducing leadership reporting time from days to hours. Developed automated ETL pipelines to extract, transform, and load business-critical data, reducing manual effort by 40% and improving data quality. Collaborated cross-functionally to integrate data-driven insights into business workflows, influencing segmentation and product development.

Machine Learning Engineer Intern at TOPS Technologies

December 1, 2022 - March 31, 2023

Developed demand forecasting models using Scikit-learn and mathematical optimization to improve inventory planning accuracy and support better resource allocation. Accelerated training cycles through hyperparameter tuning (GridSearchCV/RandomizedSearchCV), reducing iteration time from hours to minutes. Deployed ML models to AWS (EC2/S3) for scalable inference on high-volume real-time data streams. Implemented custom monitoring to detect performance degradation and trigger retraining workflows. Created reproducible Docker-based environments and standardized feature engineering practices to reduce environment-related defects by 35%.