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Patterned Learning AI

Junior Full Stack Developer React/Python

Patterned Learning AI, Oklahoma City, Oklahoma, United States, 73116


Job DescriptionJunior Full Stack Developer React/Python - onsite Job, 1+ Year Experience

Annual Income:

$62K - $76K

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.

Responsibilities:

Architect, design, and implement solutions to complex engineering problemsProvide coding expertise in Python (FastAPI and Django), React JS, TypeScript, SQL, NoSQL, and AWS to develop frontend and backend applications.Collaborate with other developers to deliver working software solutionsAssist project management with planning, product roadmap planning, and release planningAssist with code reviews and technical reviewsQualifications:

1 year of professional experience with React JS and PythonBachelor's degree in computer science, engineering, or relatedGood communication skills, both oral and writtenNice to Have experience:

Mobile app development in React NativeThirst For Tech LearningBenefits

401(k) matchingFlexible spending accountFlextimeHealth insuranceHealth savings accountPaid time offRelocation assistanceTuition reimbursement

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.