Junior Test Engineer

This is a remote position.

Junior Test Engineer - Remote Job, 1+ Year Experience

Annual Income: $65K - $80K

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:

• Collaborate with the development team to understand project requirements and develop comprehensive test plans
• Execute manual and automated tests to identify software defects and ensure the overall quality of the product
• Document test cases, test scenarios, and test results to maintain a comprehensive and up-to-date testing repository
• Identify, report, and track software bugs using issue-tracking systems, ensuring their timely resolution
• Perform regression testing to ensure previously fixed issues do not resurface
• Collaborate with cross-functional teams to drive continuous improvement in the testing process
• Stay up-to-date with the latest industry trends and technologies in software testing methodologies
  
  

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or a related field
• Strong knowledge of software testing principles, methodologies, and tools
• Familiarity with manual and automated testing techniques and tools, such as Selenium, JUnit, or similar
• Basic understanding of programming languages (Java, Python, C++, etc.) to analyze code and develop test scripts
• Excellent problem-solving skills and attention to detail
• Strong communication and collaboration skills, with the ability to work effectively in a team environment
• Ability to work independently and manage time efficiently to meet project deadlines
• Experience with Agile/Scrum development methodologies is a plus
  
  

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.

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.