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I'm Sai Nikhil Mendu, an AI/ML Engineer based in St. Louis, MO, USA, with 4+ years of experience designing, building, and deploying scalable machine learning and Generative AI solutions. I specialize in NLP and LLM systems, including Transformers, Retrieval-Augmented Generation (RAG), and PEFT/LoRA fine-tuning, and I enjoy turning complex data problems into production-ready pipelines. I have hands-on experience with MLOps (Docker, Kubernetes, CI/CD, FastAPI), cloud deployment (AWS, Azure ML), and responsible AI techniques (SHAP, LIME) to ensure model interpretability and compliance.…I'm Sai Nikhil Mendu, an AI/ML Engineer based in St. Louis, MO, USA, with 4+ years of experience designing, building, and deploying scalable machine learning and Generative AI solutions. I specialize in NLP and LLM systems, including Transformers, Retrieval-Augmented Generation (RAG), and PEFT/LoRA fine-tuning, and I enjoy turning complex data problems into production-ready pipelines. I have hands-on experience with MLOps (Docker, Kubernetes, CI/CD, FastAPI), cloud deployment (AWS, Azure ML), and responsible AI techniques (SHAP, LIME) to ensure model interpretability and compliance.

Sai Nikhil Mendu

AI Engineer, AI Developer, Data Scientist, +2

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I'm Sai Nikhil Mendu, an AI/ML Engineer based in St. Louis, MO, USA, with 4+ years of experience designing, building, and deploying scalable machine learning and Generative AI solutions. I specialize in NLP and LLM systems, including Transformers, Retrieval-Augmented Generation (RAG), and PEFT/LoRA fine-tuning, and I enjoy turning complex data problems into production-ready pipelines. I have hands-on experience with MLOps (Docker, Kubernetes, CI/CD, FastAPI), cloud deployment (AWS, Azure ML), and responsible AI techniques (SHAP, LIME) to ensure model interpretability and compliance.…I'm Sai Nikhil Mendu, an AI/ML Engineer based in St. Louis, MO, USA, with 4+ years of experience designing, building, and deploying scalable machine learning and Generative AI solutions. I specialize in NLP and LLM systems, including Transformers, Retrieval-Augmented Generation (RAG), and PEFT/LoRA fine-tuning, and I enjoy turning complex data problems into production-ready pipelines. I have hands-on experience with MLOps (Docker, Kubernetes, CI/CD, FastAPI), cloud deployment (AWS, Azure ML), and responsible AI techniques (SHAP, LIME) to ensure model interpretability and compliance.

Available to hire

I’m Sai Nikhil Mendu, an AI/ML Engineer based in St. Louis, MO, USA, with 4+ years of experience designing, building, and deploying scalable machine learning and Generative AI solutions.

I specialize in NLP and LLM systems, including Transformers, Retrieval-Augmented Generation (RAG), and PEFT/LoRA fine-tuning, and I enjoy turning complex data problems into production-ready pipelines. I have hands-on experience with MLOps (Docker, Kubernetes, CI/CD, FastAPI), cloud deployment (AWS, Azure ML), and responsible AI techniques (SHAP, LIME) to ensure model interpretability and compliance.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AI/ML Engineer at Snorkel AI

December 1, 2024 - Present

Created and deployed end-to-end ML pipelines leveraging weak supervision and programmatic labeling to accelerate model training on large-scale unstructured datasets. Built and fine-tuned NLP and structured data models using PyTorch and TensorFlow, improving accuracy and reducing manual labeling effort by 30–40%. Developed transformer-based models and embedding pipelines for text classification, entity recognition, and relation extraction tasks. Integrated Snorkel AI’s data labeling platform with client workflows, enabling scalable ML model deployment across multiple industries. Implemented MLOps best practices including Dockerized model deployment, FastAPI inference APIs, and CI/CD pipelines to ensure production reliability. Designed automated feature engineering, data validation, and preprocessing pipelines using Python (Pandas, NumPy) to enhance model performance. Monitored production model performance, executed drift detection, and incorporated explainable AI frameworks (SHAP, L

AI/ML Engineer at Fractal Analytics

June 1, 2020 - July 1, 2023

Built end-to-end predictive models (XGBoost, Random Forest, Neural Networks) for retail and telecom clients, improving demand forecasting accuracy by 22%. Engineered ETL pipelines processing more than 5M records daily using Python and SQL, reducing data preparation time by 30%. Developed customer churn prediction models, increasing targeted campaign effectiveness by 18% and improving customer retention rates. Optimized feature engineering workflows and hyperparameter tuning processes, reducing model training time by 25% while maintaining performance benchmarks. Deployed ML models using Docker and Flask APIs on AWS EC2, achieving 99.5% service uptime in production environments. Planned model monitoring dashboards using Python and Power BI, detecting data drift and reducing performance degradation incidents by 20%. Conducted A/B testing and performance evaluation experiments, improving model selection accuracy and increasing business adoption rates. Collaborated with cross-functional sta