Definición
A setting built so a model can practise a task and be scored automatically, such as a code repository with tests, a simulated website or a set of tools. Workers build environments and write the tasks and the checks that decide whether the model succeeded.
Used in: Agent and RL task roles, mostly for software engineers.
En vacantes abiertas ahora mismo
30 of the open roles we list mention “RL environment” in the title or description, on 6 platforms (as of 3 November 2026). Of those that state an hourly rate (10 distinct postings), the median is $75/hr, and the middle half pay $30 to $75.
Most of them on: Turing (13), JT AI Labs (5), micro1 (5), Scale AI (4), Terac (2), Weekday (1).
Domain Expert: Earth ScienceTuring·United States·Horario flexible
Pago no indicadohace 4 días
Software Engineer (Open Source Contributor)Weekday·India, United States·Horario flexible
$50–100/hhace 15 días
Software Engineer (Open Source Contributor)JT AI Labs·15 países
$50–100/hhace 20 días
Software Engineer (Open Source Contributor)micro1·En todo el mundo
$50–100/hhace 20 días
Machine Learning Engineers: Scenario Building for Reinforcement LearningTerac·United States
$90/hhace 2 meses
Machine Learning Fellow - Human Frontier Collective (Canada)Scale AI·Canada·Horario flexible·Doctorado
Pago no indicadohace 8 meses
Términos relacionados
Agentic taskA task in which a model works in several steps, such as searching, running code or using a website, rather than giving a single answer. ← Reward modelTérmino anterior, de la A a la Z. RLHF →Término siguiente, de la A a la Z. Glosario completoTodos los términos en una página, de la A a la Z.Abrir →