I’m Gnanesh Balusa, a Machine Learning Engineer at Amazon (Hyderabad) working on large language model fine‑tuning (SFT/DPO/RLHF), speech/ASR improvements, and efficient inference on AWS SageMaker. I build production ML systems end‑to‑end: from data selection and model training to low‑latency deployment, monitoring, and iteration. Before Amazon, I worked as a Business Analyst at McKinsey & Company and as an AI Research Software Engineer at TiHAN (IIT Hyderabad), and I’ve been a Microsoft Student Ambassador, IEEE research fellow, and active open‑source contributor. My work spans LLMs, NLP, speech emotion recognition, computer vision, MLOps, and scalable backend systems. I’ve published in Springer and IEEE, won a Best Research Paper Award at an IEEE conference, and filed a patent for MuteMemo, an invisible overlay for real‑time note‑taking in screen‑shared meetings. On the open‑source side, I’ve created tools like Canvect (CAN bus processing), Dhvagna‑NPI (offline speech transcription), and BrogsCursor (automation), with 17,900+ combined PyPI downloads used by autonomous vehicle and developer communities. Why me ?   • Get into ML/AI and software engineering roles (product companies, startups, research)   • Fine‑tune LLMs (SFT/DPO/RLHF), build RAG systems, and optimize inference   • Set up MLOps on AWS SageMaker, Docker, and Kubernetes   • Turn projects/research into strong resumes, portfolios, and GitHub profiles