Machine Learning Engineer - WFH Opportunity

About the Role

We are seeking professionals with experience in machine learning, AI research, simulation development, or technical game design to build and test scenarios in a reinforcement learning platform.

In this role, you'll configure simulation environments, define agent interaction rules and reward structures, and evaluate preliminary agent behavior. You'll also document your workflow and provide technical feedback on the platform's usability and overall process.

This opportunity is suited to professionals who understand reinforcement learning environments and are comfortable working with technical simulation tools and interfaces.

Key Responsibilities

• •Design and build structured scenarios within a reinforcement learning platform.
• •Configure environment parameters, spatial constraints, and agent interaction rules.
• •Define and work with reward structures to support reinforcement learning scenarios.
• •Test preliminary agent behavior and validate scenario configurations.
• •Document workflows, technical steps, and any challenges encountered during the process.
• •Identify platform friction points and areas where usability could be improved.
• •Provide technical feedback on platform functionality and workflow during a remote interview.

Required Qualifications

• •Professional experience in machine learning, AI research, simulation development, technical game design, or a related field.
• •Hands-on experience building simulations or reinforcement learning environments.
• •Familiarity with reinforcement learning frameworks, agent behavior, and reward structures.
• •Strong analytical and problem-solving skills.
• •Comfort working with complex technical platforms and configuration interfaces.
• •Ability to explain technical workflows clearly and provide constructive feedback during a remote interview.

Compensation and Work Arrangement

• •Contractor position paying $90 per hour.
• •Remote work within the United States.
• •Flexible schedule.

Selection Process

The selection process consists of the following stages:

• •Step 1: Application and profile submission.
• •Step 2: Profile screening.
• •Step 3: Reinforcement learning scenario-building activity.
• •Step 4: Technical feedback interview.
• •Step 5: Review and payment.