Designed and deployed scalable AI solutions, leveraging transformer models like RoBERTa, LLAMA, and GPT-4, focusing on NLP and LLMs.

Fine-tuned RoBERTa, DeepSeek, and LLaMA models on cloud platforms, achieving 94% accuracy in multi-label classification.

Deployed LLM inference services using Triton Inference Server and VLLM, integrated model endpoints, and monitored models in production to ensure reliability.

Led end-to-end AI/ML projects at Anicca Data, deploying scalable solutions on edge and cloud platforms.

Managed a 15-member team for computer vision tasks, and optimizing models for enterprise applications.

Designed and engineered data pipelines and infrastructure using AWS and GCP services.

Developed an AI pipeline that analyzed 10 million images, improving model efficiency and reducing inference time for camera health monitoring.

Implemented a real-time driver health monitoring system using wearable devices, enhancing safety by detecting driving infringements with deep learning models.

Streamlined AI datasets creation and management, ensuring data quality and reliability for AI applications, contributing to improved project outcomes.

Developed ML pipelines on AWS, monitored and configured AWS and GCP servers.

Experienced with AWS services (SageMaker, DynamoDB, Lambda, etc.) and infrastructure as code (Terraform, CloudFormation).

Ensured optimal server configurations and seamless ML deployment.