ML Engineer / AI Engineer with 2+ years of industry experience across ML systems, NLP, and large-scale data pipelines. Built and shipped production Vertex AI training pipelines (Melio), distributed PySpark ETL processing 5M+ invoices/year and graph analytics driving 15% revenue growth (Vayana Network), and researched uncertainty quantification for medical image registration at UCSD's BIAG Lab. MS CS (AI) at UC San Diego, GPA 4.0. Past projects span LLM agent evaluation under adversarial conditions, low-resource NMT with LoRA fine-tuning, and abstractive headline generation. Currently building a LangGraph-based agentic search system and a RAG-based document contradiction detector. Open to MLE, AI Engineer, Applied Scientist, and Research Engineer roles.
Remote: Yes (open to hybrid or in-person)
Willing to relocate: Yes (preferred Bay Area, NYC, Austin, and Boston)
Visa: F-1 OPT, 3 years of US work authorization (STEM OPT eligible)
Technologies: Python, PyTorch, Hugging Face, LLMs, PEFT/LoRA, RAG, LangGraph, NLP, Computer Vision, PySpark, Vertex AI, AWS, GCP, Docker, Kubernetes, W&B, Airflow, SQL, C++
Resume/CV: https://kubershahi.github.io
Email: kshahi@ucsd.edu
ML Engineer / AI Engineer with 2+ years of industry experience across ML systems, NLP, and large-scale data pipelines. Built and shipped production Vertex AI training pipelines (Melio), distributed PySpark ETL processing 5M+ invoices/year and graph analytics driving 15% revenue growth (Vayana Network), and researched uncertainty quantification for medical image registration at UCSD's BIAG Lab. MS CS (AI) at UC San Diego, GPA 4.0. Past projects span LLM agent evaluation under adversarial conditions, low-resource NMT with LoRA fine-tuning, and abstractive headline generation. Currently building a LangGraph-based agentic search system and a RAG-based document contradiction detector. Open to MLE, AI Engineer, Applied Scientist, and Research Engineer roles.