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Machine Learning Engineers: Scenario Building for Reinforcement Learning

Role overview

Qualifications

  • 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

Responsibilities

  • 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

Key facts

  • Remote from: United States
  • Fixed term
  • Machine Learning Engineer
  • English

Hard skills

Other skills

  • Problem Solving

About the company

Terac logo

Terac

Job Boards & Talent Marketplaces

Terac is an AI‑native research platform that sources participants, conducts human‑like interviews at scale, analyzes results, and pays out participants - delivering actionable insights in hours, not weeks. Product teams use Terac to run voice, video, and text interviews, concept and usability tests, and to build a living research repository they can query anytime. Our in‑house participant panel, quality controls, and self‑serve workflow mean faster cycles, higher‑quality participants, and insights that move the roadmap now, not next quarter.

Company details

IndustryJob Boards & Talent Marketplaces
Company size11 - 50

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Job description

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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Marcus Rivera

Chief Revenue Officer

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