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Abhiram Reddy Yarram is an AI/ML Engineer with over four years of experience designing, developing, and deploying machine learning and NLP solutions at scale. He has expertise in building transformer-based models, LLM-powered pipelines, and production-ready AI systems across healthcare, insurance, and engineering domains. Skilled in Python, PyTorch, TensorFlow, Hugging Face, LangChain, and cloud platforms like AWS, Azure, and GCP, Abhiram combines deep technical knowledge with a focus on delivering measurable business impact. He is passionate about creating AI solutions that improve decision-making, automate complex workflows, and enhance user experiences.…Abhiram Reddy Yarram is an AI/ML Engineer with over four years of experience designing, developing, and deploying machine learning and NLP solutions at scale. He has expertise in building transformer-based models, LLM-powered pipelines, and production-ready AI systems across healthcare, insurance, and engineering domains. Skilled in Python, PyTorch, TensorFlow, Hugging Face, LangChain, and cloud platforms like AWS, Azure, and GCP, Abhiram combines deep technical knowledge with a focus on delivering measurable business impact. He is passionate about creating AI solutions that improve decision-making, automate complex workflows, and enhance user experiences.

Abhiram Reddy Yarram

AI Engineer, Data Scientist, AI Developer, +1

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Abhiram Reddy Yarram is an AI/ML Engineer with over four years of experience designing, developing, and deploying machine learning and NLP solutions at scale. He has expertise in building transformer-based models, LLM-powered pipelines, and production-ready AI systems across healthcare, insurance, and engineering domains. Skilled in Python, PyTorch, TensorFlow, Hugging Face, LangChain, and cloud platforms like AWS, Azure, and GCP, Abhiram combines deep technical knowledge with a focus on delivering measurable business impact. He is passionate about creating AI solutions that improve decision-making, automate complex workflows, and enhance user experiences.…Abhiram Reddy Yarram is an AI/ML Engineer with over four years of experience designing, developing, and deploying machine learning and NLP solutions at scale. He has expertise in building transformer-based models, LLM-powered pipelines, and production-ready AI systems across healthcare, insurance, and engineering domains. Skilled in Python, PyTorch, TensorFlow, Hugging Face, LangChain, and cloud platforms like AWS, Azure, and GCP, Abhiram combines deep technical knowledge with a focus on delivering measurable business impact. He is passionate about creating AI solutions that improve decision-making, automate complex workflows, and enhance user experiences.

Available to hire

Abhiram Reddy Yarram is an AI/ML Engineer with over four years of experience designing, developing, and deploying machine learning and NLP solutions at scale. He has expertise in building transformer-based models, LLM-powered pipelines, and production-ready AI systems across healthcare, insurance, and engineering domains. Skilled in Python, PyTorch, TensorFlow, Hugging Face, LangChain, and cloud platforms like AWS, Azure, and GCP, Abhiram combines deep technical knowledge with a focus on delivering measurable business impact. He is passionate about creating AI solutions that improve decision-making, automate complex workflows, and enhance user experiences.

Skills

Experience Level

Expert

Expert

Expert

Expert

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Intermediate

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Intermediate

Work Experience

Associate AI Engineer at Centene Corporation

January 1, 2025 - Present

Lead the development and deployment of transformer-based models that enhance healthcare outcome predictions by 18%, enabling improved patient risk stratification and care planning. Architect scalable end-to-end ML pipelines on AWS and Azure, accelerating deployment cycles by 40% and increasing system reliability through automation and containerization. Utilize NLP libraries spaCy and NLTK to preprocess and analyze large volumes of textual data for sentiment analysis, entity recognition, and intent classification. Automate data ingestion and preprocessing workflows using Spark and Python, reducing data processing times by 35%, expediting feature engineering and model training. Use SQL to manage and query relational databases such as MySQL and Pinecone to improve data retrieval efficiency by 40%; enhance model interpretability using attention mechanisms and interactive visualizations. Collaborate with data science, engineering, and product teams to deploy AI models into production, drivi

Machine Learning Engineer at Insight Global

March 1, 2021 - July 1, 2023

Designed and deployed NLP pipelines using BERT and LangChain, which improved text classification accuracy by 20% and enhanced natural language processing capabilities in client applications. Designed and implemented interactive dashboards using Matplotlib and other visualization tools, leading to a 30% increase in stakeholder engagement. Developed cloud-integrated RESTful APIs for ML model serving, which decreased latency by 18% and improved real-time data accessibility for downstream services. Conducted extensive hyperparameter tuning and model performance evaluation, leading to a 12% increase in predictive accuracy across multiple projects. Collaborated closely with product owners and engineering teams to align ML developments with business goals, resulting in impactful solutions that enhanced client satisfaction. Work closely with cross-functional teams to understand business requirements and translate them into AI solutions.

Machine Learning Engineer at Larsen & Toubro

June 1, 2019 - February 1, 2021

Developed and maintained machine learning models for internal operations and analytics teams, focusing on predicting equipment performance and identifying early patterns of failure. Designed end-to-end data preprocessing pipelines including cleaning, feature engineering, and dataset preparation for supervised and unsupervised models. Worked with classical ML algorithms (Random Forest, XGBoost, Logistic Regression) and early deep learning models (CNN/LSTM) for structured and semi-structured data use cases. Built small-scale POCs using Python, TensorFlow, and PyTorch to evaluate model feasibility before handing them off to engineering teams for integration. Supported the deployment of models into internal applications using Flask APIs and basic Docker setups. Collaborated with cross-functional engineers to understand business challenges and translate requirements into workable ML solutions. Analyzed model performance, tuned hyperparameters, and tracked improvements using simple experimen