Hi, I'm Amit Gohel - AI Engineer at Vivansh Infotech
I am fueled by the challenge of moving AI out of the lab and into the real world. I thrive where hardware meets software, building systems that ship and solve genuine problems for users who need real results.
At a glance
Curated signals on strengths, focus areas, and how they can help.
Earned top ten recognition among 70,000 participants in a competitive national Samsung TinyML hardware innovation challenge.
Architects robust, high-concurrency production LLM and RAG systems currently serving hundreds of active users at enterprise scale.
Provides expert guidance on full-stack AI deployment, optimizing everything from edge microcontroller performance to complex cloud-native architectures.
🚀 Career trajectory
Research Foundations
Explored deep learning and wearable computing at IIT Delhi and Gandhinagar.
✦ Academic Research
✦ Neural Networks
Enterprise Deployment
Scaled AI solutions for industrial EHS platforms at Vivansh Infotech.
✦ System Architecture
✦ Enterprise Scale
💪🏻 Superpowers
Full-Stack AI Architect
Connecting edge hardware to cloud-scale intelligence
✦ Orchestrates multi-model LLM architectures for high-concurrency production environments
✦ Integrates on-device TinyML inference with cloud-native retrieval pipelines
✦ Optimizes end-to-end performance from 2KB microcontrollers to AWS clusters
Rapid Deployment Strategist
Transforming experimental prototypes into functional assets
✦ Automated manual workflows to slash production times by orders of magnitude
✦ Shipped six production-grade AI systems in under twenty-four months
✦ Maintains 95% system reliability for high-volume enterprise user bases
Edge Intelligence Specialist
Bridging physical constraints with optimized machine learning
✦ Implemented INT8 quantization for sub-2ms latency on constrained devices
✦ Deployed award-winning hardware recognized in national Samsung innovation challenges
✦ Engineered gesture recognition models with over 1,000 distinct configurations
I'm excited about
✦ Exploring advanced collaborative opportunities to build next-generation autonomous AI agents
✦ Connecting with founders building in the intersection of hardware and generative models
✦ Contributing to high-growth technical communities to push the boundaries of production AI
I can help with
✦ Architecting cost-efficient RAG pipelines for production-ready document retrieval systems
✦ Guiding the transition from prototype code to scalable, containerized cloud infrastructure
✦ Optimizing machine learning models for low-latency performance on edge computing hardware
I would love your help on
✦ Insight into scaling enterprise AI platforms to handle exponentially growing concurrent user loads
✦ Navigating strategic trade-offs between proprietary LLM integration and open-source fine-tuning
✦ Connecting with mentors experienced in technical leadership and sustainable long-term engineering growth