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Hi, I’m Akhilesh Pathi, an AI/ML Engineer with 6.5 years of hands-on experience designing and deploying scalable machine learning, generative AI, and computer vision solutions across enterprise and research environments. I specialize in building end-to-end ML systems, predictive modeling, NLP applications, and Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, and Hugging Face. I’m proficient with Python, PySpark, and cloud platforms like AWS, Azure, and GCP, with strong MLOps experience (Docker, Kubernetes, CI/CD, MLflow) for reliable deployment, monitoring, and lifecycle management.…Hi, I’m Akhilesh Pathi, an AI/ML Engineer with 6.5 years of hands-on experience designing and deploying scalable machine learning, generative AI, and computer vision solutions across enterprise and research environments. I specialize in building end-to-end ML systems, predictive modeling, NLP applications, and Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, and Hugging Face. I’m proficient with Python, PySpark, and cloud platforms like AWS, Azure, and GCP, with strong MLOps experience (Docker, Kubernetes, CI/CD, MLflow) for reliable deployment, monitoring, and lifecycle management.

Akhilesh Pathi

AI Engineer, Data Scientist, Data Analyst, +3

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Hi, I’m Akhilesh Pathi, an AI/ML Engineer with 6.5 years of hands-on experience designing and deploying scalable machine learning, generative AI, and computer vision solutions across enterprise and research environments. I specialize in building end-to-end ML systems, predictive modeling, NLP applications, and Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, and Hugging Face. I’m proficient with Python, PySpark, and cloud platforms like AWS, Azure, and GCP, with strong MLOps experience (Docker, Kubernetes, CI/CD, MLflow) for reliable deployment, monitoring, and lifecycle management.…Hi, I’m Akhilesh Pathi, an AI/ML Engineer with 6.5 years of hands-on experience designing and deploying scalable machine learning, generative AI, and computer vision solutions across enterprise and research environments. I specialize in building end-to-end ML systems, predictive modeling, NLP applications, and Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, and Hugging Face. I’m proficient with Python, PySpark, and cloud platforms like AWS, Azure, and GCP, with strong MLOps experience (Docker, Kubernetes, CI/CD, MLflow) for reliable deployment, monitoring, and lifecycle management.

Available to hire

Hi, I’m Akhilesh Pathi, an AI/ML Engineer with 6.5 years of hands-on experience designing and deploying scalable machine learning, generative AI, and computer vision solutions across enterprise and research environments.

I specialize in building end-to-end ML systems, predictive modeling, NLP applications, and Retrieval-Augmented Generation (RAG) pipelines using LangChain, LlamaIndex, and Hugging Face. I’m proficient with Python, PySpark, and cloud platforms like AWS, Azure, and GCP, with strong MLOps experience (Docker, Kubernetes, CI/CD, MLflow) for reliable deployment, monitoring, and lifecycle management.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Dell Technologies

January 1, 2024 - Present

Built scalable RAG pipelines using LlamaIndex and LangChain, integrating with Dell Object Scale to enhance semantic search across large volumes of unstructured enterprise data, improving retrieval speed by 40% and increasing relevance scores. Deployed fine-tuned LLMs using Docker and Kubernetes within Dell's AI Factory ecosystem, improving inference efficiency by 30% and optimizing resource utilization on liquid-cooled PowerEdge server clusters. Designed stateful RAG-based multi-agent workflows using LangGraph to handle real-time decisions and scalable predictive intelligence. Developed real-time object detection systems using YOLO and Vision Transformers exposed via FastAPI endpoints with monitoring for drift using MLflow. Trained and deployed ML models with XGBoost on AWS SageMaker, incorporating SHAP for explainability and implementing automated CI/CD workflows with GitHub Actions.

Data Scientist at University Of North Carolina Greensboro

January 1, 2022 - November 1, 2023

Developed and optimized predictive models for research projects using advanced frameworks like PyTorch and XGBoost; focused on feature engineering and hyperparameter tuning to improve overall model accuracy by over 15%.

Data Engineer at VMware

June 1, 2019 - December 1, 2021

Established foundational data engineering practices by designing and implementing reliable ETL pipelines using Apache Spark to ingest and process over 5 TB of monthly telemetry data, a key input for core product analytics.