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Hi, I'm Praneeth Aluru, an experienced AI/ML Engineer and Data Scientist specializing in designing, building, and deploying scalable machine learning and generative AI models. I have hands-on experience with cloud platforms like AWS, Azure, and GCP, and enjoy working on end-to-end ML workflows, including everything from data preprocessing to real-time deployment. I'm skilled with advanced NLP techniques using transformers such as BERT and GPT, and I love leveraging cutting-edge tools like LangChain and FAISS to develop intelligent applications. I thrive in collaborative environments, working cross-functionally to align AI models with business goals and drive impactful decision-making. With my background in predictive analytics, deep learning architectures, and multi-modal models, I am passionate about delivering innovative AI-powered solutions that improve operational efficiency and customer experiences.…Hi, I'm Praneeth Aluru, an experienced AI/ML Engineer and Data Scientist specializing in designing, building, and deploying scalable machine learning and generative AI models. I have hands-on experience with cloud platforms like AWS, Azure, and GCP, and enjoy working on end-to-end ML workflows, including everything from data preprocessing to real-time deployment. I'm skilled with advanced NLP techniques using transformers such as BERT and GPT, and I love leveraging cutting-edge tools like LangChain and FAISS to develop intelligent applications. I thrive in collaborative environments, working cross-functionally to align AI models with business goals and drive impactful decision-making. With my background in predictive analytics, deep learning architectures, and multi-modal models, I am passionate about delivering innovative AI-powered solutions that improve operational efficiency and customer experiences.

Praneeth Aluru

AI Engineer, Data Scientist, AI Prompt Engineer, +2

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Hi, I'm Praneeth Aluru, an experienced AI/ML Engineer and Data Scientist specializing in designing, building, and deploying scalable machine learning and generative AI models. I have hands-on experience with cloud platforms like AWS, Azure, and GCP, and enjoy working on end-to-end ML workflows, including everything from data preprocessing to real-time deployment. I'm skilled with advanced NLP techniques using transformers such as BERT and GPT, and I love leveraging cutting-edge tools like LangChain and FAISS to develop intelligent applications. I thrive in collaborative environments, working cross-functionally to align AI models with business goals and drive impactful decision-making. With my background in predictive analytics, deep learning architectures, and multi-modal models, I am passionate about delivering innovative AI-powered solutions that improve operational efficiency and customer experiences.…Hi, I'm Praneeth Aluru, an experienced AI/ML Engineer and Data Scientist specializing in designing, building, and deploying scalable machine learning and generative AI models. I have hands-on experience with cloud platforms like AWS, Azure, and GCP, and enjoy working on end-to-end ML workflows, including everything from data preprocessing to real-time deployment. I'm skilled with advanced NLP techniques using transformers such as BERT and GPT, and I love leveraging cutting-edge tools like LangChain and FAISS to develop intelligent applications. I thrive in collaborative environments, working cross-functionally to align AI models with business goals and drive impactful decision-making. With my background in predictive analytics, deep learning architectures, and multi-modal models, I am passionate about delivering innovative AI-powered solutions that improve operational efficiency and customer experiences.

Available to hire

Hi, I’m Praneeth Aluru, an experienced AI/ML Engineer and Data Scientist specializing in designing, building, and deploying scalable machine learning and generative AI models. I have hands-on experience with cloud platforms like AWS, Azure, and GCP, and enjoy working on end-to-end ML workflows, including everything from data preprocessing to real-time deployment. I’m skilled with advanced NLP techniques using transformers such as BERT and GPT, and I love leveraging cutting-edge tools like LangChain and FAISS to develop intelligent applications.

I thrive in collaborative environments, working cross-functionally to align AI models with business goals and drive impactful decision-making. With my background in predictive analytics, deep learning architectures, and multi-modal models, I am passionate about delivering innovative AI-powered solutions that improve operational efficiency and customer experiences.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Javanese

Intermediate

Work Experience

AI & Machine Learning Fellow at ElevateMe

December 1, 2024 - Present

Increased financial forecasting accuracy by 30% through the development of time series and deep learning models using TensorFlow and Azure cloud. Conducted in-depth HR data analysis to identify attrition trends and provide actionable insights, reducing manual reporting efforts by 40%. Used data visualization tools such as Tableau to create comprehensive stories that supported retention strategies. Collaborated effectively using tools like Jira, Confluence, and Slack in a professional team environment.

AI/ML Engineer at Med-kick

December 31, 2024 - July 18, 2025

Deployed Dockerized speech recognition applications integrated with AWS and S3, improving client satisfaction by 25%. Developed an 85% accurate Named Entity Recognition (NER) model for doctor-patient conversations ensuring HIPAA compliance. Leveraged Neo4j for structuring EHR data into knowledge graphs to boost decision-making efficiency by 30%. Implemented RAG pipelines for healthcare queries using LangChain, OpenAI, and FAISS, enhancing response accuracy by 25%. Designed dashboards with SQL, Power BI, and Matplotlib to raise operational efficiency by 30%. Analyzed team discussions to increase operational efficiency and product adoption.

Data Scientist – AI / ML Researcher at UNCG

December 31, 2023 - July 18, 2025

Developed TensorFlow CNN-LSTM models for ADHD detection from fMRI scans, improving accuracy by 15%. Led a team in analyzing employment impacts post-COVID using predictive analytics and statistical modeling. Enhanced NLP models through BERT and GPT integrations, increasing task efficiency by 45%. Conducted data preprocessing and segmentation optimizations for fMRI data to boost model reliability.

AI-Data Scientist at Datakalp

August 31, 2021 - July 18, 2025

Applied machine learning and NLP techniques for clinical doctor-patient conversation data, achieving 70% accuracy in NER for drug and disease classification. Created optimized ETL pipelines reducing model runtime by 95%. Led text preprocessing improvements resulting in greater model precision and accuracy in EHR data.

Machine Learning Engineer at AAIC Technologies

September 30, 2020 - July 18, 2025

Optimized e-commerce pricing models with TensorFlow and PyTorch on cloud platforms GCP and Azure, improving accuracy by 20%. Applied various ML algorithms including Random Forests and XGBoost for fraud detection and predictive modeling. Conducted exploratory data analysis and statistical testing leading to a 25% operational efficiency improvement and 10% process enhancements.

AI & Machine Learning Fellow at ElevateMe

December 1, 2024 - Present

Increased financial forecasting accuracy by 30% through the development of time series models and deep learning architectures on Azure cloud. Conducted in-depth employee data analysis uncovering attrition trends and enabling data-driven HR decisions. Reduced manual reporting efforts by 40% via exploratory data analysis and correlation analysis. Created actionable Tableau dashboards to provide insights for reducing attrition rates. Applied regression, classification, and clustering algorithms for performance optimization. Collaborated in a professional team environment using Jira, Confluence, and Slack for effective communication and project management.

AI/ML Engineer at Med-kick

December 1, 2024 - July 18, 2025

Deployed a Dockerized speech recognition ML application integrated with AWS, boosting client satisfaction by 25% and reducing deployment time by 40%. Developed an 85%-accurate Named Entity Recognition model for doctor-patient conversations adhering to HIPAA compliance. Leveraged Neo4j NoSQL to create knowledge graphs that improved analytics and decision-making efficiency by 30%. Built RAG pipelines and chatbots using LangChain, OpenAI, and FAISS, containerized FastAPI applications, and deployed them on AWS SageMaker. Designed SQL and Power BI dashboards increasing operational decision-making efficiency by 30%. Analyzed team discussions for process improvements resulting in 20% efficiency gains and increasing product adoption by 15%.

Data Scientist – AI / ML Researcher at UNCG

December 31, 2023 - July 18, 2025

Developed a CNN-LSTM model for ADHD detection using fMRI scans, improving detection accuracy by 15%. Enhanced data preprocessing and augmentation methods, boosting model reliability. Led a team to analyze COVID-19's impact on employment using statistical and predictive modeling. Conducted regression and time series decomposition for longitudinal studies. Integrated BERT and GPT transformer embeddings, improving NLP task efficiency by 45% on Azure and GCP platforms.

AI-Data Scientist at Datakalp

August 31, 2021 - July 18, 2025

Implemented deep sort algorithm for person tracking in video data. Applied machine learning and NLP on clinical doctor-patient conversation data, achieving 70% precision in Named Entity Recognition using Scispacy and PyTorch. Maintained ETL pipelines and reduced model runtime by 95% via optimized text preprocessing and spell correction. Led feature extraction and tokenization improvements, increasing NER precision by 15% for medical terms classification.

Machine Learning Engineer at AAIC Technologies

September 30, 2020 - July 18, 2025

Optimized NLP regression e-commerce pricing models using TensorFlow and PyTorch on GCP and Azure, improving accuracy by 20%. Employed Random Forests, XGBoost, and deep learning algorithms to enhance credit card fraud detection, increasing pricing accuracy by 15%. Conducted exploratory data analysis, statistical hypothesis testing, and correlation analysis leading to 25% operational efficiency improvements. Delivered actionable insights aligned with business strategies improving process efficiency by 10%.