This is a remote position.
Senior Full stack MERN engineer - Remote Job, 3-5+ Year Experience
Annual Income: $97K - $121K
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.
Role Description
This is a full-time remote role for a Full-stack MERN engineer. The engineer will be responsible for the development and maintenance of web applications. Day-to-day tasks include designing user interactions on web pages, developing server-side APIs, and working with cross-functional teams to develop features that meet customer needs.
Qualifications
- Full-Stack Development and Software Development skills
- Back-End Web Development skills
- Front-end development skills, including proficiency with HTML, CSS, and JavaScript
- Proficiency in MERN stack (MongoDB, Express, ReactJS, NodeJS)
- Experience with CSS
- Proficiency with RESTful APIs, curl
- Excellent problem-solving and debugging skills
- Familiarity with Git and agile development methodologies
- Bachelor's or Master's degree in Computer Science, Software Engineering, or related field
- Experience with Healthcare IT, Electronic Health Records (EHR) and Health Information Exchange (HIE) is a plus.
Additional Requirements
- We are looking for a candidate to work in the EST (Boston timezone).
- Conversational English is a must
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.