I’m Nihat Rzayev, an early-career AI/ML engineer and software QA practitioner from Baku, working at the intersection of Python-based machine learning, LLM-enabled applications, and reliable software testing. I enjoy building and evaluating models, running controlled experiments (including Transformer long-context studies), and turning data and requirements into practical, reproducible results. On the engineering side, I’ve contributed to services using embeddings and cosine similarity with FastAPI, PostgreSQL, and GPT-4o-mini, and I’ve developed async workflows with validation, rate limiting, and Docker-based automation. On the QA side, I translate acceptance criteria into strong test coverage—covering functional, regression, smoke, integration, API, and UAT support—and I document findings clearly in Jira/Confluence while verifying fixes with developers and stakeholders.…I’m Nihat Rzayev, an early-career AI/ML engineer and software QA practitioner from Baku, working at the intersection of Python-based machine learning, LLM-enabled applications, and reliable software testing. I enjoy building and evaluating models, running controlled experiments (including Transformer long-context studies), and turning data and requirements into practical, reproducible results. On the engineering side, I’ve contributed to services using embeddings and cosine similarity with FastAPI, PostgreSQL, and GPT-4o-mini, and I’ve developed async workflows with validation, rate limiting, and Docker-based automation. On the QA side, I translate acceptance criteria into strong test coverage—covering functional, regression, smoke, integration, API, and UAT support—and I document findings clearly in Jira/Confluence while verifying fixes with developers and stakeholders.WWWW…