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Job Post Details

Software Engineer for AI Training Data (Swift) - job post

G2i Inc.
Montevideo, Departamento de Montevideo

Información del empleo

Así es como las especificaciones del empleo se alinean con tu perfil.

Tipo de empleo

  • Por Contrato


Montevideo, Departamento de Montevideo

Descripción completa del empleo

Accepted Locations

We are accepting applicants from the US, Canada, and most countries in LATAM and Europe. We are accepting some countries in Africa and Asia. For the full list of accepted locations click here. This work is 100% remote.

Loom Video

Our Founder/CEO, Gabe Greenberg, created a more in depth Loom video that we highly recommend you watch! Check it out here:

Job Overview

We are currently seeking Swift Developers for project-specific roles focused on RLHF. This role will play a key part in our reinforcement learning from human feedback (RLHF) initiatives, contributing to cutting-edge projects.

You’ll join an expert annotation team to create training data for for the worlds most advanced AI models. No previous AI experience is necessary. You'll get your foot in the door with one of the biggest players in the AI/LLM space today. We are seeking software engineers with 4+ years of experience to train AI large language models, helping cutting-edge generative AI models write better code. Projects typically include discrete, highly variable problems that involve engaging with these models as they learn to code. We currently have 200+ roles open!

What Will I Be Doing?

  • Evaluating the quality of AI-generated code, including human-readable summaries of your rationale

  • Solve coding problems, writing functional and efficient code

  • Writing robust test cases to confirm code works efficiently and effectively

  • We asked the technical project manager to go into even more detail and this is how he answered: It is solving coding challenges, creating instructions to help others, reviewing the code before it goes into the model, and there's a ton of variety in the projects. We have everything from "which piece of Python code is better?" to "make a full mobile application using this chatbot, and improve the chatbot's responses afterwards to make it faster"

Contract Length

  • This project is expected to last until the end of September and you'll be able to continue to work on other projects (though likely not in Swift)

  • You can end the contract at any time.

Flexible Schedules

  • Developers can set their own hours - ideal candidates will be interested in spending 15+ hours a week. They will be with teams, so strong performers will adapt to the urgency of projects and stay engaged, but incredibly flexible on working hours.

  • Take a 3 hour lunch, no problem. You are paid according to time spent on the platform, which is calculated in the coding exercises, as opposed to tracking your own hours.


  • US: $50 /hr

  • Brazil: $28.70/hr

  • Egypt: $22.05/hr

  • Phillipines: $25.55/hr

  • All other countries: $35/hr

  • Expectations are 15+ hours per week however there is no upper limit. We have engineers working 20-40 hrs per week and some that are working 40+ hours per week. You can work as much as you want to. You'll get paid on a weekly basis. You get paid per hour of work done on the platform.

Interview Process

We've created a 3.5 hour screening and onboarding process to join as a Software Engineer for AI Training Data which can be accomplished in 1 week or less. We purposely perform most of these steps asynchronously because most of the RLHF work is async and self guided. After you apply, if you look like a good fit we'll provide you access to the G2i dashboard to go through this simple screening process.

Step 1: Learn in depth about the role (35 min)

Step 2: Perform a simple RLHF code review (35 min)

Step 3: Receive platform credentials, pass ID verification (5 min), and join an optional live onboarding with our team (60 min)

Step 4: Perform a production level RLHF task (75 min) "aka the final interview"

Join us: Based on your final interview, you'll will put you on the right difficulty RLHF project

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