Gaurav Pathak
I am a software engineer specializing in computer vision, generative AI, and production machine learning systems.
About
I am a software engineer specializing in computer vision, generative AI, and production machine learning systems. I enjoy training and deploying detection and tracking models, integrating LLMs and VLMs for intelligent verification, and building real-time ML pipelines that work reliably across cloud and edge environments. My experience includes developing RAG chatbots, voice agents, vehicle analytics solutions, and backend services using Python, computer vision, modern APIs, and cloud infrastructure.
I am also passionate about creating practical products that combine strong engineering with friendly user experiences. From building a voice-first communication coach to deploying surveillance analytics on Jetson and Raspberry Pi devices, I like turning complex AI capabilities into useful applications. I bring a full-stack mindset, hands-on deployment experience, and a continuous interest in improving model performance, system reliability, and developer workflows.
- 2 years' experience
- Joined September 2026
Industry experience
- Software & Internet
- Computers & Electronics
- Transportation & Logistics
- Retail
- Professional Services
Work experience
Trained and deployed YOLO, DETR, and OBB detection and classification models for surveillance analytics, with multi-object tracking using ByteTrack, DeepSORT, and BoT-SORT. Integrated Qwen, Gemma, Gemini, CLIP, and SigLIP as LLM and VLM verification layers for weapon detection and vehicle attribute extraction. Developed RAG chatbots and voice conversational agents using Whisper, LLMs, text-to-speech, ChromaDB, and FAISS. Built FastAPI and PostgreSQL backend services, deployed them on AWS with Docker and Nginx, created Streamlit dashboards, and implemented edge inference on Raspberry Pi and NVIDIA Jetson devices using MQTT.
Developed backend services integrating Google Vision API for vehicle number plate, model, and color extraction, achieving reported detection accuracy of 95% and reducing manual verification time by 40%. Built RESTful APIs and frontend views for processed analytics data, improving internal visibility by 20%. Worked on performance tuning and data validation logic that increased overall system reliability by 25%.
Education
Certifications and awards
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