Moulik Shah

Hands‑on ML and LLM engineering: Moulik’s portfolio and repos show practical projects across NLP (prompt‑tuning / LoRA), speech emotion recognition, and applied ML systems for finance (news sentiment trader), indicating strengths in building end‑to‑end ML pipelines and adapting LLM techniques to constrained setups. vercel+2

Full‑stack and production engineering experience: his personal site and project descriptions demonstrate experience deploying models and building full‑stack applications (React, Flask/Gradio, cloud deployment), suggesting an emphasis on shipping usable ML products, not just research prototypes. vercel+1

Academic and research engagement at NYU: listed as a graduate student and Machine Learning Researcher (V‑Lab / Action Lab) at NYU Stern, combining coursework with lab research — positioning him as a student‑researcher bridging academic ML and applied industry projects. nyuactionlab

Diverse industry internships and short‑term roles across data engineering and ML: résumé listings (Cornspring, Miko, Sykes & Ray, Bipolar Factory, Myraa, Ares) and student leadership roles show a mix of quantitative, data‑engineering, and ML engineering experience gained through internships and campus projects. vercel+1