Description

Own the optimization and deployment of computer-vision algorithms, specifically YOLO-based models, for edge environments. You will fine-tune and retrain off-the-shelf models, applying quantization and distillation to reduce latency and footprint. You will containerize FastAPI-based web services using Docker and publish inference results to message brokers. You will operate and maintain the production architecture on Kubernetes and Google Cloud Platform. You will contribute to scalable Python and TypeScript services.

Responsibilities

• Fine-tune and retrain YOLO-based object detection models for specific edge deployment needs.
• Apply model optimization techniques including quantization and distillation to improve performance on constrained hardware.
• Containerize FastAPI web services using Docker and integrate them with message brokers for result publishing.
• Manage and operate production infrastructure on Kubernetes and Google Cloud Platform.
• Develop and maintain scalable backend services using Python and TypeScript.

Required Skills

• 5+ years of experience in computer-vision algorithms, with a strong focus on YOLO-based models.
• Proficiency in Python and TypeScript for building scalable architectures.
• Strong experience with Docker for containerization and service management.
• Hands-on experience with Kubernetes for orchestration and deployment.
• Practical experience with Google Cloud Platform (GCP) services.
• Understanding of model optimization techniques such as quantization and distillation.

Preferred Skills

• Experience with FastAPI framework for building web services.
• Familiarity with message broker systems for asynchronous result publishing.

Key Skills

Education

Any Graduate