Remote Software Engineer for AI Training Data (School Specific)

Description:

• This position is for a Software Engineer focused on AI Training Data, specifically for school-specific candidates.
• The role is 100% remote and accepts candidates from Ivy League colleges, top 50 colleges in the US, or the University of Waterloo in Canada.
• Candidates must be from specific countries as outlined in the job posting.
• You will join an expert annotation team to create training data for advanced AI models, with no previous AI experience necessary.
• The job involves evaluating the quality of AI-generated code and writing robust test cases to ensure code efficiency and effectiveness.
• The contract is long-term with no specified end date, and you can terminate it at any time, although a commitment of 6 months is preferred.
• Flexible working hours are offered, with a minimum expectation of 15+ hours per week and the option to work 40+ hours.
• Developers can set their own schedules and are paid based on time spent on the platform, calculated through coding exercises.
• The interview process includes applying through a form, background review, group call, boot camp, and quality score assessment for job placement.

Requirements:

• Candidates must be attending or have graduated from an Ivy League college, a top 50 college in the US, or the University of Waterloo in Canada.
• Professional programming experience is not required, but completion of introductory computer science and data structure courses is necessary.
• Complete fluency in the English language is required.
• Candidates must have the ability to articulate complex technical concepts clearly and engagingly.
• Excellent attention to detail and the ability to maintain consistency in writing are essential.

Benefits:

• The position offers a long-term contract with the flexibility to end it at any time.
• Developers can work flexible hours and set their own schedules.
• Compensation is based on time spent on the platform, allowing for a pay structure that reflects actual work done.
• The opportunity to work on projects as they become available after successful completion of the interview process.