Junior System Administrator

Job Description
Junior System Administrator - Hybrid (3 days in office) Job, 1+ Year Experience

Annual Income: $55K - $79K

A valid work permit is necessary in the US

About us: Patterned Learning is a platform that aims to help developers code faster and more efficiently. It offers features such as collaborative coding, real-time multiplayer editing, and the ability to build, test, and deploy directly from the browser. The platform also provides tightly integrated code generation, editing, and output capabilities.

Job description

A System Administrator is someone who maintains, upgrades and manages software, hardware, and networks. Resourcefulness is a necessary skill in this role. You should be able to diagnose and resolve problems quickly. Being patient when communicating with various interdisciplinary teams and users would be best. Your goal will be to ensure our technology infrastructure runs smoothly and efficiently.

What you'll need to be successful:
• Proven experience as a System Administrator, Network Administrator, or similar role
• Experience with databases, networks (LAN, WAN), and patch management
• Knowledge of system security (e.g., intrusion detection systems) and data backup/recovery
• Ability to create scripts in Python, Perl, or other language
• Familiarity with various operating systems and platforms
• Resourcefulness and problem-solving aptitude
• Excellent communication skills
• BSc/Ba in Information Technology, Computer Science, or a related discipline; professional certification (e.g., Microsoft Certified Systems Administrator (MCSA)) is a plus

Why Patterned Learning LLC?

Patterned Learning can provide intelligent suggestions, automate repetitive tasks, and assist developers in writing code more effectively. This can help reduce coding errors, improve productivity, and accelerate development.

The pattern recognition is particularly relevant in the context of coding. Neural networks, intense learning models, are commonly employed for pattern detection and classification tasks. These models simulate human decision-making and can identify patterns in data, making them well-suited for tasks like code analysis and generation.