Duc Anh Ho

- Developed and deployed an end-to-end LLM fine-tuning API for dataset upload, dataset processing, fine-tuning, deployment, and benchmarking. - Optimized LLM training/inference with Ray clusters, scaling for large datasets. - Developed FastAPI microservices for LLM APIs in Kubernetes environments. - Applied rate limiting to prevent API overload. - Automated CI/CD pipelines using GitLab CI. - Monitored API health and performance with Grafana. - Managed YAML files for Kubernetes deployments.

Developed ML-based building classification system utilizing Computer Vision techniques for efficient urban planning, customized UNet and DeepLabv3+ models to accurately identify building amenities from geospatial data. Researched large language model (LLM) and developed Text-to-Image synthesis projects using Transformer-based models, generating realistic images from textual descriptions. Collaborated with a team to preprocess data, fine-tune the model, and deploy a powerful tool of Computer vision and LLM

Built robust data pipelines for advanced instance segmentation and object detection models, using FastAPI for efficient REST APIs. Employed PostgreSQL for data storage, applying outlier detection and imputation for high-quality datasets. Utilized Kafka for microservices communication, connecting FastAPI services for seamless data flow. Designed and automated CI/CD pipelines using GitHub Action and ensuring smooth model deployment. Created optimized DB structures for efficient data retrieval and storage.

Focus: Machine Learning Engineering, Grade: 1.3