Annual Income: $60K - $65K, Onsite
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
Overview
The
Application Support Engineer I is a role within our Software Support division.
The ideal candidate for this position will have strong technical skills and a
passion for troubleshooting. This is a customer facing position, so this
individual must have strong communication and customer service skills. Our team
remotely supports production environments all around the globe to resolve
issues and minimize the impact to production. The software support team
troubleshoots both software and hardware issues. As an Application Support
Engineer I you will find yourself troubleshooting in-house applications, 3rd
party applications, data mining, report building, writing and working with
complex queries, database management, indexing, and potentially promoting a
software fix. Are you afraid of falling into the rut of doing the same thing
day in day out? No problem is the same and no day is the same. You will be able
to take pride in your work and be personally responsible for keep our customers
multi-million dollar operations running smoothly.
Job
Functions
Travel
Requirements
Preferred
Skills and Required Qualifications
In
addition to exciting work at a growing company, we offer the following
benefits:
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 the
development process.
The
pattern recognition is particularly relevant in the context of
coding. Neural networks, especially deep 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.
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