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$144k – $315k per year (Estimated)
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Terac is an AI-powered market research and human data platform headquartered in the United States. Founded by Zachary Baker and Jack Blair, the enterprise operates an infrastructure layer connecting AI agents with verified human domain experts and research participants. Operating on a B2B SaaS and usage-based API business model, Terac automates qualitative research by using conversational voice and text AI agents to recruit participants, moderate interviews, collect feedback, and synthesize structured data insights in real time for product, marketing, and frontier AI research teams.

What We're Researching

We're hiring AI researchers and machine learning engineers to participate in building worlds within a reinforcement learning platform. This work directly influences how agents interact with complex, simulated environments during their training cycles. Your technical expertise will help us refine the tools and interfaces used to create robust testing scenarios.

How It Works

You will connect to our remote platform to design and construct specific scenarios for reinforcement learning agents. Throughout the session, you will configure environmental parameters, define spatial constraints, and run preliminary agent interactions to test your setup. You will document your workflow and note any friction points encountered while structuring the environment. Finally, you will participate in an interview to share your feedback on the platform's overall usability.

Who This Is For

This study targets professionals with hands-on experience in simulation design and reinforcement learning environments. We welcome machine learning engineers, AI researchers, simulation developers, and technical game designers accustomed to RL frameworks. Candidates should be highly comfortable configuring complex platform interfaces and defining structured agent scenarios.

What You'll Do

  • Design and build specific scenarios within a remote reinforcement learning platform

  • Configure environmental parameters and define agent interaction rules

  • Test initial agent behaviors to validate your scenario structure

  • Walk us through your workflow and highlight areas for platform improvement

Who Should Apply

  • Professional experience in machine learning or artificial intelligence research

  • Hands-on background in building simulations or reinforcement learning environments

  • Familiarity with configuring platform interfaces and defining reward structures

  • Comfortable articulating technical feedback during a remote interview

Compensation

$90 per hour

Ready to participate?

Start your paid interview now

About Terac

Terac is building the world's largest pool of vetted human experts for AI. Researchers, AI labs, and product teams use Terac to recruit, screen, and pay study participants across industries, languages, and skill sets.

Learn more at terac.com or on YouTube at @jointerac.

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