Job Summary :

We are looking for an experienced AI/ML Developer with strong expertise in Computer Vision, Deep Learning, and Real-Time Video Analytics to develop advanced Intelligent Transportation Systems (ITS) solutions. The role involves building and optimizing AI models for traffic surveillance, incident detection, vehicle analytics, and traffic enforcement applications.

Experience Requirement :

- 5+ years of professional experience in AI/ML development, including 2+ years in Computer Vision or Video Analytics.

- Experience developing and deploying real-time AI models for visual-based ITS or industrial automation products.

- Experience working with large-scale data and multi-camera video analytics systems in production environments.

Key Responsibilities :

- Develop AI-based video analytics models for incident detection such as stopped vehicles, wrong-way driving, pedestrian entry, congestion, and accidents.

- Develop solutions for vehicle classification, speed estimation, number plate recognition, and traffic violation detection.

- Build and optimize object detection, motion tracking, and event recognition pipelines for live video feeds.

- Integrate AI models with ITS systems including VIDES, ATCC, AVC, TMCS, ANPR, and VASD.

- Develop data labeling, annotation, and dataset management tools for model training and evaluation.

- Deploy and optimize AI models on edge platforms such as NVIDIA Jetson and Intel Movidius.

- Monitor model performance and implement fine-tuning and retraining strategies.

- Collaborate with backend and frontend teams for API integration, alert management, and visualization.

- Research and implement advanced Computer Vision and multimodal AI techniques.

Tech Stack :

- Languages & Frameworks : Python, OpenCV, TensorFlow, PyTorch, Keras

- Deep Learning : CNN, R-CNN, YOLOv8, SSD, ResNet, DeepSORT

- Computer Vision : Object Detection, Tracking, Event Detection

- Real-Time Video : RTSP, RTMP, ONVIF

- APIs & Microservices : REST API, GraphQL, gRPC

- Databases : MySQL, Pinecone DB, Vector DB

- Edge AI : TensorRT, ONNX, OpenVINO

- Infrastructure : Linux, Docker, Git, Apache Kafka, RabbitMQ, AWS SQS

- Model Evaluation : Precision, Recall, F1-Score, Latency

Preferred Skills :

- ITS, Smart Highway, or Smart City domain experience

- Traffic enforcement rules and incident classification workflows

- C#, .NET, Node.js, or React.js

- Sensor Fusion : Radar, LiDAR, and Video

- MLOps and automated model deployment

- Cloud-based AI inference platforms : Azure, AWS, or GCP