Description

You will develop, optimize, and deploy computer vision models for edge environments. Your work focuses on refining YOLO-based architectures and integrating them into scalable production systems.

Responsibilities

• Fine-tune and retrain off-the-shelf YOLO models for object detection tasks.
• Apply quantization and distillation techniques to optimize models for edge deployment.
• Containerize FastAPI-based web services using Docker and publish results to message brokers.
• Operate and maintain production architecture on Google Cloud Platform using Kubernetes.
• Contribute to scalable system design using Python and TypeScript.

Required Skills

• Strong experience with computer vision algorithms, specifically YOLO-based models.
• Proficiency in Python and machine learning frameworks for model training and optimization.
• Hands-on experience with Docker for containerizing applications.
• Practical exposure to Kubernetes for orchestration and GCP for cloud infrastructure.
• Understanding of model optimization techniques such as quantization and distillation.
• Ability to deploy FastAPI-based services and integrate with message brokers.

Preferred Skills

• Experience with TypeScript in scalable architectures.
• Background in edge deployment strategies.

Key Skills

Education

Any Graduate