About Arbius:

Arbius is at the forefront of revolutionizing the AI landscape by decentralizing machine learning and inference. This groundbreaking platform harnesses the power of global GPU miners, creating a decentralized network that generates new tokens and supports AI models and tasks. Arbius is not just about technology; it's a movement towards democratizing AI, ensuring transparency, accessibility, and innovation through a community-driven approach.

Job Title: ML Dockerized Container Specialist

Location: Remote

Company: Arbius

Website: https://arbius.ai/

Role Overview:

We are seeking a highly skilled and motivated ML Dockerized Container Specialist to join our innovative team. The ideal candidate will have extensive experience with ML dockerized containers, particularly in understanding and modifying inference parameters within a COG container from seed. This role is crucial in ensuring our AI models run seamlessly across different machines with the same hardware configuration, and in verifying network CID matches.

Responsibilities

• Container Management: Expertly manage ML dockerized containers, focusing on the initialization, configuration, and deployment of COG containers.
• Inference Optimization: Understand and modify inference parameters to optimize performance and accuracy of AI models within COG containers.
• Network Verification: Ensure that the AI models operate correctly on the network by matching Content Identifiers (CIDs) for verification across machines with identical hardware.
• Troubleshooting and Debugging: Diagnose and resolve issues related to container performance and network discrepancies.
• Collaboration: Work closely with our team to implement and maintain robust container solutions.

Qualifications

• Technical Expertise: Proven experience with ML dockerized containers, especially in managing and modifying COG containers (Containers for Machine Learning) . Proficiency in Docker, including creating, managing, and deploying containers.
• AI and ML Knowledge: Strong understanding of machine learning concepts and inference parameters.
• Networking Skills: Familiarity with network configurations and verification processes.
• Problem-Solving: Excellent troubleshooting skills with a proactive approach to identifying and resolving issues.