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Ramesh Naidu

@rameshnaidu

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AI/ML Engineer with expertise in intelligent systems and machine learning.

United States

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What I'm looking for

I seek a role that fosters innovation and collaboration, allowing me to leverage my AI/ML expertise to solve complex problems and contribute to impactful projects.

As an AI/ML Engineer with over 5 years of hands-on experience, I specialize in crafting and implementing intelligent systems across diverse domains. My expertise lies in building and deploying machine learning models using Python, TensorFlow, PyTorch, and Scikit-learn. I have a strong focus on deep learning, natural language processing, computer vision, and MLOps, managing full-cycle ML workflows from data preprocessing to production deployment.

In my current role at Adobe, I successfully built and launched a personalized recommendation system that boosted sales by 15%. My work involves applying advanced techniques like K-Means clustering and hyperparameter tuning to enhance model accuracy and relevance. I am adept at engineering robust ETL pipelines and deploying machine learning models on AWS, ensuring real-time monitoring and performance metrics through MLOps practices.

Previously, as a Data Scientist at Anblicks, I improved supply-demand forecasting accuracy by 38% and automated inventory recommendations, significantly reducing manual intervention. My experience as a Sr. Data Analyst at Genpact further honed my skills in predictive modeling and data visualization, enabling me to communicate insights effectively to stakeholders. I am passionate about leveraging my skills to drive impactful solutions in the AI/ML landscape.

Experience

Work history, roles, and key accomplishments

Current

Generative AI Engineer

Current

Adobe

Aug 2024 - Present (11 months)

Built and launched a personalized recommendation system by integrating collaborative filtering, content-based techniques, autoencoders, and LLMs, leading to a 15% boost in sales and a noticeable rise in customer satisfaction. Streamlined model lifecycle management by implementing MLOps practices, including automated CI/CD pipelines (GitHub Actions), containerization (Docker), orchestration (Kubern

Python TensorFlow Keras scikit learn AWS Sagemaker Lambda Redshift Cloudwatch Prometheus Docker Kubernetes Terraform GitHub Actions)LLMs)ETL Pyspark Scala SQL Apache Spark

Data Scientist

Anblicks

Apr 2022 - Present (3 years 3 months)

Designed machine learning pipeline using ARIMA, Random Forest, XGBoost, and LSTM (TensorFlow/Keras), improving supply-demand forecasting accuracy by 38% and reducing medical supply stockouts across 15+ hospital departments. Automated inventory recommendations and purchase order generation, reducing manual intervention by 70% and shortening procurement cycle time by 2.5 days, integrated directly wi

ARIMA Random Forest XGBoost TensorFlow Keras AWS EC2 S3 Hyperparameter Tuning Cross Validation

Sr. Data Analyst

Genpact

Jun 2019 - Present (6 years 1 month)

Built and fine-tuned predictive models to estimate property sale prices using a diverse set of machine learning and deep learning algorithms, including Linear Regression, Random Forest, Gradient Boosting, XGBoost, and LightGBM. Developed 20+ dynamic and static data visualizations with Matplotlib, Seaborn, Plotly, and Dash to present key insights and model outcomes, enabling clear communication wit

Random Forest Gradient Boosting XGBoost LightGBM NLP Tokenization Lemmatization Stemming NER NLTK SpaCy TextBlob ETL Python Scala SQL Matplotlib SeaBorn Plotly Dash A B Testing Scipy

Education

Degrees, certifications, and relevant coursework

Southern Arkansas University

Master of Science, Computer Science

Pursued a Master of Science in Computer Science, focusing on advanced topics and research within the field. Developed a strong foundation in theoretical and practical aspects of computer science.