Generative Ai Machine Learning

Eshwar Ramavath

Kingsville, TX

361-***-**** — *.***********@*****.*** — linkedin.com/in/eshwar-kiran-rathod-4a0b611ab — eshwarrathod.in

Professional Summary

Graduate student in Computer Science with research and industry experience in generative AI. Skilled in design- ing, training, and optimizing large-scale models including VAEs, GANs, and diffusion models. Strong foundation in deep learning, scalable systems, and model deployment using modern ML tools and infrastructure. Technical Skills

• Languages: Python, C++, SQL, Bash

• Frameworks: PyTorch, TensorFlow, JAX

• Generative Models: VAEs, GANs, Diffusion, Autoregressive Transformers

• ML Techniques: DDP, mixed-precision training, pretraining, fine-tuning

• Tools: Docker, Git, Weights & Biases, Slurm, Kubernetes

• Infrastructure: Multi-GPU/TPU training, REST/gRPC APIs, CI/CD pipelines Experience

Graduate Research Assistant – Generative AI Texas A&M University - Kingsville Jan 2024 – Apr 2024

• Led research on generative scene modeling using VAEs and latent diffusion architectures.

• Implemented distributed training with DDP and mixed-precision to reduce resource overhead.

• Evaluated generative quality using industry-standard metrics such as FID and Inception Score. AI Intern – Applied Machine Learning LTI Mindtree, Hyderabad Jun 2023 – Dec 2023

• Developed scalable microservices integrating LLMs via RESTful APIs and gRPC protocols.

• Improved system performance through request batching, response caching, and load balancing. Projects

Latent Diffusion for Scene Generation

Technologies: PyTorch, Apex, CUDA

• Designed a latent diffusion pipeline capable of generating high-resolution, coherent scenes.

• Integrated memory-efficient training techniques to support 4K image synthesis on multi-GPU systems. Video Prediction using Transformers

Technologies: TensorFlow, TPU

• Implemented an autoregressive video transformer for motion prediction in driving datasets.

• Quantitatively assessed model accuracy using Dynamic Time Warping and cosine similarity metrics. Education

Master of Science in Computer Science Texas A&M University - Kingsville, TX Expected: May 2025

Bachelor of Technology in Computer Engineering Kakatiya University Graduated: 2022

Certifications

• Generative AI with Large Language Models – DeepLearning.AI

• Advanced PyTorch for Research – Udacity

Achievements

• Winner – TAMU Autonomous Systems Hackathon 2023

• Awarded NVIDIA Research Grant for work on generative AI systems

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