About the role
We are looking for an AI/Computer Vision Engineer to build and optimize real-time video analytics solutions for safety-critical environments. The ideal candidate should have experience in developing, training, and deploying deep learning models for object detection, tracking, and video understanding. You will work closely with product, cloud, and engineering teams to deliver scalable AI solutions.
Develop, train, and optimize computer vision models for real-time object detection and tracking.
Work with YOLO, RT-DETR, or similar object detection frameworks.
Prepare, clean, and annotate datasets for model training.
Fine-tune pre-trained models and improve detection accuracy.
Evaluate model performance using precision, recall, mAP, and latency metrics.
Optimize inference for edge devices and GPU-based deployments.
Integrate AI models into production applications.
Work with video streams (RTSP, CCTV, IP Cameras).
Collaborate with software engineers for deployment and API integration.
Troubleshoot model performance and continuously improve detection accuracy.
Maintain documentation and experiment tracking.
Computer Vision
Object Detection
Image Classification
Object Tracking
Instance Segmentation (preferred)
Video Analytics
PyTorch
TensorFlow/Keras
OpenCV
Ultralytics YOLO
CNN Fundamentals
Python
NumPy
Pandas
Object-Oriented Programming
Data Annotation
Dataset Preparation
Data Augmentation
Docker
REST APIs
GPU Optimization
Linux
RequirementsPreferred Experience
·Experience with live video processing.
·Experience deploying AI models on NVIDIA GPUs.
·Familiarity with DeepStream or TensorRT.
·Knowledge of MLOps fundamentals.
·Experience using Git and Agile methodologies.
·Bachelor's degree in Computer Science, AI,
Electronics, or a related field.
·2–4 years of hands-on experience in AI/ML or
Computer Vision.
·Strong problem-solving and analytical skills.
Python •
PyTorch • OpenCV • Ultralytics YOLO • TensorRT • Docker • Linux • Git • REST
APIs • AWS