About
I build AI systems that don't just perform , they explain themselves. As an AI Research Scientist at Mercedes-Benz R&D India and Compleren AI Labs, I work at the intersection of explainable AI, computer vision, and responsible ML, applying these to autonomous driving perception. My technical foundation spans the full ML stack - PyTorch, HuggingFace, MONAI, LangChain, FastAPI, and Docker , with hands-on experience in model compression (LoRA, pruning, quantization, SVD decomposition), hybrid semantic search (FAISS, BM25, dense retrieval), and multi-turn conversational AI. I've fine-tuned SLMs like Qwen3 and Phi-3 for code intelligence and Text-to-SQL tasks, and built evaluation frameworks for long-context LLM reasoning. At IISc Bangalore, I completed coursework spanning deep learning for CV and NLP, stochastic models, and optimization , with a publication accepted at ACM ASIACCS 2026 on ML-based cryptographic security. I'm drawn to roles where research and production meet: designing systems that are accurate, interpretable, and trustworthy. Whether it's improving lead conversion with CatBoost at Scaler, benchmarking lane detection models against synthetic CARLA data, or stress-testing LLMs through structured evaluation pipelines, I care about building things that hold up under scrutiny. Currently exploring full-time Data Scientist and AI Scientist opportunities where I can contribute across the model lifecycle , from experimentation and fine-tuning to deployment and monitoring.
Work experience
AI Research Scientist at Mercedes-Benz Research and Development India, Jan 2026 - Present · 8 mos, Bengaluru, Karnataka, India
Data Science Intern at Scaler, Jun 2025 - Dec 2025 · 7 mos, On-site
