I have strong experience in Python scripting and building cloud/desktop applications and libraries for ML models/servers using technologies like PyTorch, PySpark, Pandas, and Flask/Django. My expertise extends to various ML models, including Computer Vision and NLP recognition/generation, where I have trained and fine-tuned models from scratch with correct data engineering and science. I am proficient in content generation models and services, combining them into a single pipeline with effective prompt engineering and parameter adjustments. My experience also includes deploying ML models onto cloud servers and edge devices, optimizing them into lightweight models while conducting performance analysis with high insight metrics. I have a solid background in MLOps tools and platforms, including Terraform and Nvidia Triton Server, and I am skilled in configuring GCP and AWS services for ML training and serving instances. Additionally, I have experience in architecting ML Ops from scratch, including resource planning, project estimation, and mentoring team members.
Led the AI development pipeline and production deployment for the app filtering and recommendation based on app descriptions and metadata.
Worked on LLM-based domain specified and business information analysis assist Chat/QA bot/reporter building.
Played with text classification models for contextual text blobs.
Worked on several projects with professional experience in Data Science and ML|DL solutions development.
From scratch building an AI vision and time-series model in the startup environment.
Backend service development and internal data tools development.
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