---
title: "Tejus Kavishwar - Computer Vision Research Engineer in Gurugram | Tal"
description: "Meet Tejus Kavishwar, Computer Vision Engineer · Detection, Segmentation & Tracking · Edge AI (TensorRT/ONNX) · Traffic & Smart City Systems · Open to Opportunities based in Gurugram."
image: "https://tal.club/meet/tejus-2/share-image"
---

# Tejus Kavishwar on Tal

## Headline

Computer Vision Engineer · Detection, Segmentation & Tracking · Edge AI \(TensorRT/ONNX\) · Traffic & Smart City Systems · Open to Opportunities

## About

I build computer vision systems that work in the real world \- not just in research notebooks\. Over 2\+ years at Metafusion, joining early as part of the founding team, I helped shape and ship the company's core CV product stack from scratch: intelligent traffic monitoring, video incident detection, multi\-lane free\-flow tolling, and ANPR pipelines deployed across live infrastructure\. My work spans the full modern vision stack\. On the modelling side: object detection \(YOLO, DETR\), instance segmentation \(SAM, Mask R\-CNN\), multi\-object tracking \(ByteTrack, SORT\), and pose estimation\. On the deployment side: TensorRT and ONNX optimization for edge hardware, C\+\+ OpenCV pipelines for latency\-critical systems, and Docker/Kubernetes for production delivery\. I've also integrated Vision\-Language Models into production environments using vLLM and Ollama \- connecting multimodal reasoning into existing CV pipelines where classical detection alone wasn't enough\. I care about systems that are fast, reliable, and actually deployed \- not demo\-ware\. If you're building something in computer vision, edge AI, or video analytics and want to talk, reach me at tejuskavishwar78@gmail\.com

## Location

Gurugram

## Work experience

Computer Vision Research Engineer at Metafusion, Jun 2024 \- Present · 2 yrs 1 mo, Noida, Uttar Pradesh, India, • Architected and shipped three production video analytics suites \- ITMS \(traffic management\), VIDES \(incident detection\), and MLFF \(free\-flow tolling\) \- by building end\-to\-end pipelines combining YOLO/DETR detection, ByteTrack/SORT multi\-object tracking, and ANPR with OCR, resulting in live deployments processing concurrent camera streams across smart city and highway infrastructure\. • Optimized detection and segmentation models \(YOLO, Mask R\-CNN, SAM\) for edge hardware deployment using TensorRT and ONNX quantization, and maintained C\+\+ OpenCV pipelines for latency\-critical scenarios where Python overhead was not acceptable\. • Extended production CV pipelines with Vision\-Language Model \(VLM\) integration via vLLM and Ollama, enabling multimodal scene reasoning in scenarios where classical detection alone was insufficient \- deployed using Docker and Kubernetes\.

Computer Vision Intern at Metafusion, Oct 2023 \- May 2024 · 8 mos, India

Data Science Intern at Innomatics Research Labs, Feb 2023 \- Jun 2023 · 5 mos, Hyderabad, Telangana, India, • Built and evaluated supervised ML models \(classification and regression\) using Scikit\-learn and Pandas, improving baseline performance by 20% through feature engineering and hyperparameter tuning\. • Conducted EDA across 10\+ structured datasets, surfacing statistical patterns that informed model selection and preprocessing decisions\.

Computer Vision Intern at Awiros, Jul 2022 \- Aug 2022 · 2 mos, Gurugram, Haryana, India, • Implemented real\-time face detection and recognition pipeline using OpenCV and deep learning, integrated into live surveillance video streams for production testing\. • Built a pose estimation module for a fitness application \(push\-up counter\), gaining hands\-on experience with human keypoint detection and temporal consistency on video\.

## Education

Bachelor of Technology \- BTech, CSE \(AI and ML\), Maharshi Dayanand University \(MDU\), Rohtak

[View the original profile](https://tal.club/meet/tejus-2)

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