ProgressSoft Corporation

• Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion). • Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs. • End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring. • LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements. • AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines. • Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team. • Mentor junior engineers and contribute to technical direction and engineering best practices.

• Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion). • Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs. • End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring. • LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements. • AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines. • Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team. • Mentor junior engineers and contribute to technical direction and engineering best practices.