Log In
Sign Up
United States
Patterned Learning Career Looking for Entry Level Java developer (US) at Chicago, IL Full Time
This is a remote position.
Entry Level Java developer (US) – Remote Job, 1+ Year Experience
Annual Income: $55K – $65K
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
An entry-level Java developer with Java development experience or similar academic background.
The key skills are
- Java, J2EE, Full stack Development, Spring, MVC, Hibernate, and Web Apps development.
- HTML, CSS, JavaScript, Angular, React, and Node Etc.
- Knowledge of relational databases (e.g. SQL Server, Oracle)
- Experience working on Cloud Technologies and Environments (i.e. AWS, Azure, Google Cloud)
- Good knowledge of Object object-oriented design and development.
- Impeccable software engineering habits (e.g. unit and regression testing, code reviews, etc.)
- Knowledge of developing complex, high-performance enterprise software.
- BE/BTech or MS in CS, CE, SE, ECE – recent Graduate is required.
- Good written and verbal communication skills.
- A positive outlook, an interest in adapting to new technologies, a passion for software engineering, and the ability to work as part of a team.
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.
