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I am a results-driven AIML Engineer with over 3 years of experience in developing, deploying, and optimizing AI/ML solutions across enterprise and research-driven environments. I specialize in Large Language Models (LLMs), Generative AI, MLOps, and Data Engineering, with a track record at Molina Healthcare and HCLTech. I thrive on applying cutting-edge tools and frameworks to deliver scalable, production-ready AI solutions. I excel at collaborating with global teams to drive innovation and accelerate AI adoption. I have hands-on experience with RAG pipelines, knowledge retrieval, model deployment on Azure, and end-to-end ML lifecycles, including ETL, feature engineering, and monitoring. I’ve mentored junior engineers and contributed to internal deployment frameworks to reduce iteration cycles.…I am a results-driven AIML Engineer with over 3 years of experience in developing, deploying, and optimizing AI/ML solutions across enterprise and research-driven environments. I specialize in Large Language Models (LLMs), Generative AI, MLOps, and Data Engineering, with a track record at Molina Healthcare and HCLTech. I thrive on applying cutting-edge tools and frameworks to deliver scalable, production-ready AI solutions. I excel at collaborating with global teams to drive innovation and accelerate AI adoption. I have hands-on experience with RAG pipelines, knowledge retrieval, model deployment on Azure, and end-to-end ML lifecycles, including ETL, feature engineering, and monitoring. I’ve mentored junior engineers and contributed to internal deployment frameworks to reduce iteration cycles.

Mahendra Avudiyappan

AI Engineer, Data Scientist, Front-End Developer, +2

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I am a results-driven AIML Engineer with over 3 years of experience in developing, deploying, and optimizing AI/ML solutions across enterprise and research-driven environments. I specialize in Large Language Models (LLMs), Generative AI, MLOps, and Data Engineering, with a track record at Molina Healthcare and HCLTech. I thrive on applying cutting-edge tools and frameworks to deliver scalable, production-ready AI solutions. I excel at collaborating with global teams to drive innovation and accelerate AI adoption. I have hands-on experience with RAG pipelines, knowledge retrieval, model deployment on Azure, and end-to-end ML lifecycles, including ETL, feature engineering, and monitoring. I’ve mentored junior engineers and contributed to internal deployment frameworks to reduce iteration cycles.…I am a results-driven AIML Engineer with over 3 years of experience in developing, deploying, and optimizing AI/ML solutions across enterprise and research-driven environments. I specialize in Large Language Models (LLMs), Generative AI, MLOps, and Data Engineering, with a track record at Molina Healthcare and HCLTech. I thrive on applying cutting-edge tools and frameworks to deliver scalable, production-ready AI solutions. I excel at collaborating with global teams to drive innovation and accelerate AI adoption. I have hands-on experience with RAG pipelines, knowledge retrieval, model deployment on Azure, and end-to-end ML lifecycles, including ETL, feature engineering, and monitoring. I’ve mentored junior engineers and contributed to internal deployment frameworks to reduce iteration cycles.

Available to hire

I am a results-driven AIML Engineer with over 3 years of experience in developing, deploying, and optimizing AI/ML solutions across enterprise and research-driven environments. I specialize in Large Language Models (LLMs), Generative AI, MLOps, and Data Engineering, with a track record at Molina Healthcare and HCLTech. I thrive on applying cutting-edge tools and frameworks to deliver scalable, production-ready AI solutions.

I excel at collaborating with global teams to drive innovation and accelerate AI adoption. I have hands-on experience with RAG pipelines, knowledge retrieval, model deployment on Azure, and end-to-end ML lifecycles, including ETL, feature engineering, and monitoring. I’ve mentored junior engineers and contributed to internal deployment frameworks to reduce iteration cycles.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Work Experience

AIML Engineer at Molina Healthcare, USA

May 1, 2025 - Present

Developed and deployed production-grade Generative AI solutions and LLM-based applications for enterprise and consumer products. Worked with LLaMA, GPT APIs, Hugging Face Transformers, and RAG pipelines for knowledge-intensive applications. Designed and implemented MLOps pipelines using MLflow, Docker, Azure ML, and CI/CD, reducing deployment time by 40%. Optimized CNNs, UNet, and Autoencoders for image/video analytics and multimodal AI. Collaborated with cross-functional teams to integrate AI solutions with Microsoft Copilot, Ollama, and internal APIs. Performed ETL, feature engineering, and preprocessing with Spark, Pandas, and NumPy. Mentored junior engineers on ML lifecycle and cloud deployment.

AIML Research Assistant at DePaul University, Chicago, IL

June 1, 2024 - November 1, 2024

Developed and deployed real-time anomaly detection for pharmacy workflows, reducing delays and improving prescription verification efficiency. Processed and engineered 115K+ records into scalable ML feature pipelines, increasing ETL speed by 30%. Trained deep learning models in PyTorch, boosting macro-F1 score by 8.9 points and minority-class recall by 15%. Reduced false positives by 22% through model optimization, class balancing, and hyperparameter tuning. Containerized ML training and inference pipelines using Docker and MLflow, increasing throughput by 11% and reducing queue delays by 18%. Implemented automated model evaluation and validation pipelines to ensure production-grade deployment standards.

ML Engineer at HCLTech, India

August 1, 2021 - November 1, 2023

Designed, trained, and deployed ML and deep learning models for enterprise-scale projects in healthcare, finance, and retail. Built predictive models using PyTorch, TensorFlow, Scikit-learn for classification, regression, and anomaly detection. Developed ETL pipelines and data preprocessing workflows using Pandas, NumPy, and Spark, ensuring clean and reliable datasets. Implemented MLOps practices including Dockerized model deployment, MLflow tracking, and CI/CD integration on Azure & AWS. Assisted in LLM and NLP projects, integrating Hugging Face Transformers for chatbots and document summarization tasks. Worked with SQL and NoSQL databases for data storage, querying, and feature extraction.