G2i - Senior/Staff Software Engineer | AI Task Creation

From Silver.dev

Estamos ayudando a los de G2i a conseguir trainers y task creators para laboratorios de AI, que incluyen a OpenAI y SpaceX.

Las tareas son unidades de trabajo para entrenar a los modelos y se paga por tarea completada efectivamente. Las tareas toman entre 1 y 2 días en completarse, y los creadores de tareas más efectivos llegan a completar más de 30 tareas mensualmente.

El trabajo es async y lo podés manejar a tu tiempo, pero sí requiere varias horas de trabajo y onboarding. Presten atención a las instrucciones de G2i. Pueden aplicar directamente con ellos en este link , o aplicar en nuestra plataforma y nosotros manejamos su aplicación.

Pueden escuchar a Gabriel Greenberg directamente sobre el trabajo en el siguiente Loom:

About the role

G2i is hiring senior and staff-level software engineers to build the coding tasks a frontier AI lab uses to train its models. Each completed task pays $1,000 USD.

Most AI training work is annotation: engineers pick up a task someone else wrote and evaluate it. This role is one step earlier. You design and build the tasks themselves, which takes a different skill set from typical product engineering.

What you'll do

• Design and build realistic, challenging software engineering tasks that frontier models will be trained and evaluated on

• Write tasks across codebases of very different sizes, from a few files to large multi-service projects

• Work mainly in TypeScript, Python and Go

• Revise your tasks based on feedback from G2i reviewers and team leads until they meet the lab's quality bar

• Work mostly on your own, with support from reviewers and a shared engineer channel

Who we're looking for

We're hiring two kinds of engineers. Both are welcome to apply.

• Engineers who have built AI training tasks before (top priority). You've designed and built tasks or environments for training models at a frontier lab or a data lab. Contractor experience counts. What matters is that you built tasks, not only annotated, reviewed or evaluated tasks someone else wrote.

• Very strong senior, staff or principal engineers who haven't done this yet. You have deep, hands-on skill in TypeScript, Python and/or Go, and you learn new kinds of work fast. You may need a few extra days in training to learn the format, and that's expected.

For both profiles:

• Senior to principal-level engineering experience

• Strong code reading and writing skills, without relying on AI tools

• Clear written English, since tasks and reviewer feedback are written

Pay

You're paid per completed task, not by the hour.

• Training project: if you pass, you're paid $600 USD and join the core team.

• Each completed task after training: $1,000 USD

Based on early internal data, top performers finish 1 to 2 tasks a day, mid-level performers about 1 every other day, and others 1 to 2 a week. A task usually takes 4 to 10 hours.

If you don't pass the training, it doesn't count against you for other G2i AI projects. Those may open to you separately.

Hiring process

There are no live technical interviews. The steps are:

• Apply through the link below.

• Take-home assessment. It's designed to take about 90 minutes. Taking 4 to 6 hours is fine and won't lower your score, because quality matters more than speed. It doesn't expire, but the sooner you finish it, the sooner you can start.

• Background check. This usually takes 24 to 48 hours in the US and Canada. In some countries it can take more.

• Offer. It's usually sent within a day after your background check clears.

• Training project. You build one task with guidance from reviewers and team leads. You have up to 7 days. Engineers who have built tasks before often finish in 1 to 2. If you pass, you're paid $600 and join the core team. If you don't, you're out of this project, and it's unpaid.

Hours and contract

• Contract: independent contractor, fully remote. Either side can end it at any time.

• Hours: 40 a week is ideal. Part-time is welcome: 20 a week is preferred, and 10 is the minimum.

• Schedule: flexible. You can work any day of the week, and some overlap with North American time zones is preferred.

• Keep your current job: you don't need to leave a full-time role to join part-time.

• Length: this is a project-based engagement, not a permanent role. When it ends, G2i often has other frontier AI projects available.