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AI/ML Engineer with 4 years of experience specializing in NLP, Generative AI, and LLM applications. Built and deployed RAG workflows, AI chatbots, and sentiment analysis pipelines at scale using BERT, Hugging Face Transformers, LangChain, OpenAI APIs, and FastAPI. Experienced end-to-end across the ML lifecycle—from model architecture/training and optimization (pruning, quantization) to AWS production deployments. Strong MLOps background with Docker, Kubernetes, CI/CD, and model monitoring to improve reliability and reduce deployment and inference costs.…AI/ML Engineer with 4 years of experience specializing in NLP, Generative AI, and LLM applications. Built and deployed RAG workflows, AI chatbots, and sentiment analysis pipelines at scale using BERT, Hugging Face Transformers, LangChain, OpenAI APIs, and FastAPI. Experienced end-to-end across the ML lifecycle—from model architecture/training and optimization (pruning, quantization) to AWS production deployments. Strong MLOps background with Docker, Kubernetes, CI/CD, and model monitoring to improve reliability and reduce deployment and inference costs.

Meetkumar Patel

AI Engineer, Data Engineer, Data Scientist, +2

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AI/ML Engineer with 4 years of experience specializing in NLP, Generative AI, and LLM applications. Built and deployed RAG workflows, AI chatbots, and sentiment analysis pipelines at scale using BERT, Hugging Face Transformers, LangChain, OpenAI APIs, and FastAPI. Experienced end-to-end across the ML lifecycle—from model architecture/training and optimization (pruning, quantization) to AWS production deployments. Strong MLOps background with Docker, Kubernetes, CI/CD, and model monitoring to improve reliability and reduce deployment and inference costs.…AI/ML Engineer with 4 years of experience specializing in NLP, Generative AI, and LLM applications. Built and deployed RAG workflows, AI chatbots, and sentiment analysis pipelines at scale using BERT, Hugging Face Transformers, LangChain, OpenAI APIs, and FastAPI. Experienced end-to-end across the ML lifecycle—from model architecture/training and optimization (pruning, quantization) to AWS production deployments. Strong MLOps background with Docker, Kubernetes, CI/CD, and model monitoring to improve reliability and reduce deployment and inference costs.

Available to hire

AI/ML Engineer with 4 years of experience specializing in NLP, Generative AI, and LLM applications. Built and deployed RAG workflows, AI chatbots, and sentiment analysis pipelines at scale using BERT, Hugging Face Transformers, LangChain, OpenAI APIs, and FastAPI.

Experienced end-to-end across the ML lifecycle—from model architecture/training and optimization (pruning, quantization) to AWS production deployments. Strong MLOps background with Docker, Kubernetes, CI/CD, and model monitoring to improve reliability and reduce deployment and inference costs.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

AI/ML Engineer at Accenture

October 1, 2024 - Present

Contributed to production ML pipeline architecture in Python to automate risk assessment workflows, processing 10,000+ applications monthly at 92% accuracy and reducing turnaround time by 40%. Assisted in building RAG workflows and internal AI chatbot prototypes using LLMs, vector embeddings, and FastAPI, including retrieval and policy-informed access. Applied model optimization techniques—pruning, quantization, and hyperparameter tuning—across deployed frameworks (TensorFlow, PyTorch) to reduce inference time by 60% and lower AWS cloud costs by $25,000 annually. Supported MLOps practices and operations using Docker, Kubernetes, and MLflow in CI/CD pipelines, helping reduce deployment time from 2 weeks to 3 days. Implemented model monitoring, drift detection, and maintenance protocols in production environments; contributed to forecasting pipelines for near-real-time inference workloads on AWS. Collaborated with cross-functional teams including data engineers, actuarial analysts,

Data Science & AI Engineer at Equitable Bank

June 1, 2022 - August 1, 2024

Developed and trained classification, regression, and recommendation model architectures using TensorFlow, PyTorch, and scikit-learn, improving prediction accuracy by 18% through feature engineering and hyperparameter tuning. Built computer vision models for image classification using CNNs and transfer learning (ResNet-50, VGG-16), reducing manual processing time by 30%. Executed NLP pipelines including sentiment analysis, text classification, and RAG systems using Transformers, BERT, LangChain, and OpenAI APIs to enhance customer insight extraction. Built a sentiment analysis pipeline using BERT, spaCy, and Hugging Face Transformers to process 100,000+ customer interactions monthly, contributing to a 23% improvement in satisfaction scores. Designed time-series forecasting models to support business planning and risk evaluation workflows and improved trend prediction reliability across operational datasets. Performed statistical analysis, A/B testing, and hypothesis testing; communic