This role exists to capture the valuable signal in network engineers' heads, which currently disappears after a ticket is closed. The goal is to build a system that allows models to learn to think like network engineers, enabling Meter to autonomously manage thousands of customer networks without adding more engineers. The core problem is that unlike software development, where LLMs benefit from structured data like Git commits and issue trackers that capture human reasoning, network engineering lacks such a corpus. When a network engineer diagnoses a problem, their reasoning remains in their head, inaccessible to models. The successful candidate will build the equivalent of Git and GitHub for network engineering: a structured, queryable record of what the network looked like, what the expert notice, and why they made the call they made.
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
11-50 employees