$100-150/hrAs published by the platform.
This remote contract role centers on building physics simulation environments in MuJoCo that teach AI agents to move and manipulate objects. It suits experienced practitioners who combine robot control, reinforcement learning, and physics simulation expertise.
$100-150/hr
Pay as published by the platform. It is not a guarantee of income or hours.
The platform has not published which countries are eligible for this job.
You apply on Alignerr, Labelbox's expert network: create a profile, complete an AI-led interview and skills assessment, then get matched to projects in your field.
Official posting: https://www.alignerr.com/jobs/089ba86b-3df3-4782-bc9f-5783da03a5ab
Last checked on October 8, 2026.
This remote contract role asks you to build and refine MuJoCo simulation environments that teach AI agents locomotion, manipulation, and multi-agent coordination. It is aimed at experienced robotics and machine learning practitioners who are comfortable with physics simulation, reinforcement learning, and robot control.
This contract role centers on building and refining MuJoCo physics simulation environments where AI agents learn locomotion, manipulation, and multi-agent coordination. It suits experienced robotics and machine learning practitioners who work on reinforcement learning, robot control, and simulation debugging, mostly on their own in an asynchronous, remote setting.
As a Machine Learning Engineer, you will evaluate and improve how AI models reason about machine learning systems, including training dynamics, evaluation design, and deployment strategies. You will write prompts to test model reasoning, identify subtle errors in AI outputs, and provide correct solutions based on real practitioner experience.
This study invites machine learning engineers and AI researchers to build test scenarios on a remote reinforcement learning platform. Participants set environmental parameters, define spatial constraints and agent interaction rules, run preliminary agent tests, and then share usability feedback in an interview. It is aimed at people with hands-on experience in simulation design and RL environments.
Posted September 3, 2026
You will evaluate the methodological quality and scientific rigor of machine learning tasks designed to train and test models at a cutting-edge AI laboratory. You will provide structured feedback on experimental design, model selection and evaluation protocols, critiquing claims against observed results.
Posted August 28, 2026
Join a network of machine learning experts to access occasional jobs with AI laboratories and companies. You will contribute to training and evaluating models, creating tasks based on real-world scenarios, and providing domain feedback for AI research. This program is aimed at engineers with solid experience in machine learning model development and capable of working independently on remote projects.
Posted February 27, 2026
