Headline

AI/ML Engineer · NLP & GenAI | LLMs · RAG · VLMs | MTech CSE @ IIIT Bangalore | Codeforces Expert · LeetCode Knight | Open to Roles in AI/ML & Research

About

I'm an AI/ML engineer and MTech Computer Science student at IIIT Bangalore, passionate about building intelligent systems at the intersection of NLP, Large Language Models, and real-world applications. My work spans clinical AI, autonomous driving, and conversational systems. At Augnito, I built ML-driven NLP pipelines for Clinical Documentation Improvement, extracting medical entities from unstructured text using advanced language modeling. At Bosch Global Software Technologies, I integrated Vision-Language Models into an autonomous driving stack — cutting object detection processing time by 15% and projecting a 20% gain in scene understanding accuracy after benchmarking 10+ multimodal architectures. Beyond industry work, I trained a Transformer model from scratch on 25K+ emotionally rich dialogues to build an empathetic chatbot — evaluated via BLEU scores and perplexity — and serve as a Teaching Assistant for the Machine Learning course at IIIT Bangalore. On the competitive programming side, I'm a Codeforces Expert and LeetCode Knight, which has sharpened my algorithmic thinking and systems design instincts — skills I bring directly to ML pipeline optimization and model efficiency. I'm actively seeking full-time roles in AI Engineering, ML Engineering, Generative AI, and Research Engineering. If you're building something meaningful with AI, let's connect.

Location

Ahmedabad

AI stack

antigravity

codex

claudecode

Work experience

NLP Research Intern at Augnito, Jan 2026 - Present · 8 mos, Bengaluru, - Engineered an ML-driven NLP pipeline for Clinical Documentation Improvement (CDI), leveraging transformer-based language models to capture contextual relationships in clinical text at scale. - Optimized medical named entity recognition (NER) by designing advanced preprocessing strategies and domain-specific fine-tuning, improving extraction precision of clinical entities from unstructured EHR data. - Applied Retrieval-Augmented Generation (RAG) techniques to enhance semantic information retrieval, reducing hallucination risk in clinical AI outputs. - Collaborated with cross-functional teams to iterate on model tuning strategies, improving downstream CDI task performance across multiple clinical document types.

Teaching Assistant — Machine Learning at International Institute of Information Technology Bangalore, Aug 2025 - Dec 2025 · 5 mos, Bengaluru, - Selected as TA for the Machine Learning course at IIIT Bangalore, supporting instruction for graduate-level students on supervised learning, neural networks, and optimization techniques. - Designed problem sets and evaluation rubrics, and conducted doubt-clearing sessions to reinforce conceptual understanding of ML fundamentals.

Applied Research Intern at Bosch Global Software Technologies, May 2025 - Jul 2025 · 3 mos, Bengaluru, - Integrated a novel Vision-Language Model (VLM) into a production autonomous driving perception stack, reducing object detection processing latency by 15% and improving system reaction speed under real-world conditions. - Benchmarked and analyzed 10+ state-of-the-art multimodal architectures (including CLIP-based and instruction-tuned VLMs), identifying architectural improvements projected to increase scene understanding accuracy by 20%. - Designed and implemented a systematic evaluation framework to compare VLM performance across diverse driving scenarios, enabling data-driven model selection for safety-critical applications. - Collaborated with research and engineering teams to align VLM outputs with downstream decision-making modules in the autonomous driving stack.

Software Engineer Intern at TatvaSoft, Jan 2024 - Jun 2024 · 6 mos, Ahmedabad, - Led full-stack development of a scalable appointment scheduling web application, reducing average user booking time by 40% through streamlined UX workflows and optimized data flows. - Engineered and tuned backend systems in .NET, achieving a 25% reduction in server response time under high-load conditions, improving platform reliability and user experience. - Implemented RESTful APIs and database optimizations to support concurrent user operations, delivering a production-ready system within a 6-month timeline.

Artificial Intelligence Engineer at Scale AI, Jan 2022 - Jan 2024 · 2 yrs 1 mo, Remote, - Fine-tuned and evaluated large-scale language models using advanced RLHF and NLP techniques, boosting conversational accuracy by 25% across multiple production AI applications. - Developed and stress-tested conversational AI systems built on transformer architectures, reducing model error rates by 30% through targeted performance analysis and iterative prompt optimization. - Contributed to data quality pipelines for LLM training, annotating and curating high-quality datasets used in production model updates.

Education

Master of Technology - MTech, Computer Science, International Institute of Information Technology Bangalore

Bachelor of Technology - BTech, Computer Engineering, LJ Institute of Engineering and Technology

Public links

github: https://github.com/ParvGatecha