Jun 2024 – May 2025 · 11 mos · Basking Ridge, New Jersey, United States · Remote

Nov 2022 – Aug 2023 · 9 mos · Los Angeles, California, United States · Remote

• ❇ Enhanced AI-driven content generation efficiency by 25% through leading the integration of transformers within AWS microservices.
• ❇Developed a Chrome extension using Python, JavaScript, and NodeJS, boosting content quality and generation speed by 40%.
• ❇Utilized Docker for scalable and reliable deployment across cloud environments via AWS ECS and Fargate.
• ❇Improved project management and team collaboration through implementing effective development methodologies.
• ❇Optimized content creation for various use cases by conducting A/B testing with models like LLaMA-13B, Flan-T5, Vicuna-13B, and GPT-3.5.
• ❇Broadened audience reach by using GCP's Google Translate API for multi-language content translation.
• ❇Ensured high-quality, error-free content by implementing NLP algorithms with BERT, RoBERTa, and DistilBERT for grammar correction, significantly enhancing user trust.

Jun 2022 – Mar 2023 · 9 mos · Los Angeles, California, United States

• ❇Automated article generation for digital marketing using AWS Lambda, NodeJS, and API Gateway achieving a 60x reduction in operational costs.
• ❇Integrated NLP and TensorFlow to analyze and generate over 130K high-quality articles within a week, improving content strategy.
• ❇Utilized DynamoDB for managing large datasets, ensuring efficient data access and manipulation for content generation processes.
• ❇Fine-tuned advanced NLP models like BERT, RoBERTa, ALBERT, and DistilBERT for contextual understanding, improving the relevance and quality of generated articles.
• ❇Explored generative models including GPT-3, GPT-Neo, GPT-J, and GPT-NeoX, to diversify content creation, ensuring a wide range of engaging and unique articles.
• ❇Leveraged Flan-T5 and T5 Codegen for specific content generation tasks, optimizing for both efficiency and creativity in article production.
• ❇Developed custom dataset models with Gensim, enhancing thematic accuracy and alignment with marketing goals.
• ❇Employed MLOps practices with Git and Docker to streamline the development, training, and deployment of machine learning models, facilitating continuous improvement and collaboration.

Dec 2021 – Dec 2022 · 1 yr · Hyderabad, Telangana, India

• ❇Developed a sophisticated image classification system using Faster R-CNN, tailored for the nuanced detection of cancerous cells in histopathological images, leveraging TensorFlow for model training and optimization.
• ❇Engineered a custom segmentation solution with Detectron2, enabling precise delineation of tumor boundaries in medical scans. This approach utilized QuPath for image management and Groovy for scripting complex analysis workflows, significantly enhancing the quality of medical image analysis.
• ❇Implemented YOLOv5 for the automated screening of pathological slides, achieving unprecedented speed and accuracy in identifying critical diagnostic markers, integrated with OpenCV for real-time image processing and enhancements.
• ❇Led the integration of MLOps practices, utilizing Docker for containerization and AWS for model deployment, ensuring scalable and robust AI solutions in clinical settings.
• ❇Mentored a diverse group of 10-20 junior colleagues (first and second-year students) on multiple ML and DL projects, fostering a collaborative learning environment and enhancing the team's overall AI expertise and project execution capabilities.

Nov 2021 – Mar 2022 · 4 mos · Hyderabad, Telangana, India

• ❇ Coded a YOLOv5-based real-time object detection system using Python and TensorFlow, integrated with Streamlit for a user-friendly interface, achieving 90% accuracy.
• ❇ Engineered a deep learning model for speech recognition with PyTorch, achieving 95% accuracy, deployed in an Army Walkie Talkie emulator.
• ❇ Utilized Docker and AWS for deploying scalable and efficient machine learning models, reducing operational costs and improving resource utilization.
• ❇ Leveraged SQL and SQLite for efficient data storage and retrieval, enhancing system performance and data management.
• ❇ Conducted A/B testing to optimize the model's performance, resulting in enhanced accuracy and user satisfaction.

Oct 2021 – Oct 2021 · 0 mo · Hyderabad, Telangana, India

• The internship was designed to help you gain a practical insight into the work of KPMG.
• ❇ The following 3 tasks to be given were Data Quality Assessment where you prepare the data for analysis and clean it.
• ❇ Data Insights where you work on getting meaningful insights from the data.
• ❇ Data Insights and Presentation where you prepare visualisations using Tableau, Power BI to gain more knowledge about the data.

Dec 2020 – Jan 2021 · 1 mo · India

• ❇ Write code to collect, crunch and analyze data from various internal and external sources.
• ❇ Build machine and tune learning models using Python and scikit-learn.
• ❇ Create linkages between various data within business intelligence software to enable predictive modeling and trend analysis.

Aug 2020 – Sep 2020 · 1 mo · Hyderabad, Telangana, India

• ❇ Write code to collect, crunch and analyze data from various internal and external sources.
• ❇ Build machine and tune learning models using Python and scikit-learn, Computer Vision using ML, Image processing using Deep Learning, Regression-based project, Classification, Natural language processing, Web scraping
• ❇ Create linkages between various data within business intelligence software to enable predictive modeling and trend analysis.