Key Responsibilities

• CV/AI Models Deployment: participating in development and leading the deployment of computer vision models along with other custom AI models for analysis. Focus on enhancing capabilities for player tracking and interference analysis.System Configuration Management: Deploy, configure, and manage servers and systems ensuring high availability and performance. Use automation tools and scripts in Python/YAML to streamline processes along with Managing the usage of GPUs and Edge use-cases deployments.CI/CD Pipeline Management: Design, develop, and maintain continuous integration and deployment pipelines, ensuring smooth and reliable deployment of applications and services.
• Cloud Infrastructure Management: Oversee and own the infrastructure on AWS cloud platforms while utilize Azure DevOps tools to maintain and scale operations.
• Distributed Systems Management: Manage distributed computing systems including databases, storage layers, and compute processes.
• Troubleshooting and Support: Provide expert-level troubleshooting for complex production issues. Develop automated logging, monitoring, and alerting systems to enhance reliability and performance.
• Expert understanding of Unix/Linux based operating system.
• Excellent problem solving, critical thinking and communication skills
• Performance Evaluation: Conduct rigorous performance evaluations of the models using relevant metrics, making continuous improvements to achieve state-of-the-art results.
• Integration: Collaborate with software development teams to integrate the developed models into sports analysis platforms and applications.
• Operational Support and Release Management: Support production operations, manage software releases, and maintain parity across development, staging, and production environments.Innovation and Development: Prototype and develop solutions using cloud-native architecture to meet application needs.
• Design and implement a robust monitoring infrastructure.
• Strong oral and written skills along with storytelling skills

Qualifications:

• Bachelor’s or master’s degree in computer science, Machine Learning,
• or related field (Ph.D. preferred).
• Extensive experience in managing cloud environments AWS and implementing Azure CI/CD pipelines.
• Experience with data preprocessing, augmentation, and annotation for computer vision tasks.
• Familiarity with GPU computing and cloud-based AI services (AWS, Azure, GCP).
• Excellent problem-solving and communication skills.
• Ability to work effectively in a collaborative team environment.
• Experience in deploying and managing computer vision and AI models is highly desirable.