Founder @Rola Labs | Building @TasteMap


Remote

San Francisco, California, United States








Bachelor of Technology - BTech, Computer Science
Veer Surendra Sai University Of Technology ( Formerly UCE ), Burla
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Building toward a future where physical spaces are as accessible, interactive, and adaptive as digital ones. Interested in creating AI-driven systems that help people navigate, connect with, and experience the real world more naturally. Currently exploring generative AI, agentic systems, and human-centered product experiences.
Bengaluru
antigravity
gemini
hugging face
langchain
mcp
obsidian
Founder at TasteMap, Mar 2026 - Present · 7 mos
Co-founder · AI & Product Lead at Rola Labs, Apr 2025 - Present · 1 yr 6 mos, Remote
Full Stack | Deep Learning Engineer at platform.ai, Apr 2020 - Aug 2024 · 4 yrs 5 mos, San Francisco, California, United States, Led end-to-end development of real-world AI systems across healthcare, food-tech, and fashion domains. • Built scalable ML pipelines and backend infrastructure deployed on Google Cloud (Cloud Run, Functions) • Delivered real-time implant detection (85%+ accuracy) and food doneness classification (90%+ accuracy) • Implemented self-supervised learning (BYOL, SimCLR), zero-shot search using CLIP, and generative AI (diffusion models, U-Net) • Optimized infrastructure, reducing latency and server costs through GCP service migration • Mentored junior ML fellows; led research on noisy-label training and robust loss functions • Collaborated with product and engineering teams to deliver analytics dashboards, case-sharing flows, and user feedback loops Tools & Technologies: Python, ReactJS, PyTorch, Flask, FastAPI, GCP, Docker, Kubernetes, CI/CD
Machine Learning Fellow at Fellowship.AI, Jan 2020 - Mar 2020 · 3 mos, • Built a CNN-based wound classification model trained on a dataset of 1,000+ images (78% accuracy) • Led data collection, cleaning, and preprocessing to ensure class balance and image quality • Researched noise-robust training using CoTeaching, Symmetric Cross Entropy (SCE), and LID-Paced Loss • Delivered analysis and benchmarks on robust model training under weak labeling conditions Focus Areas: Deep Learning, Computer Vision, Noisy Label Learning, PyTorch, Data Preparation
Bachelor of Technology - BTech, Computer Science, Veer Surendra Sai University Of Technology ( Formerly UCE ), Burla