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Machine Learning Engineers: Scenario Building for Reinforcement Learning

Terac · company site3 weeks ago

1 · Can you apply from United States?

Open to United States
United StatesExact words from the ad · found 29 Sep 2026

2 · What reaches you

1Pay
2Platform fee− $0
3Payout fee · Wise− $0 – $6.11
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$15,594 / month
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Wise fee page, checked 25 Sep 2026
Fixed fees assume one withdrawal a month.

3 · How you get paid

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First money
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4 · Your working hours

Not stated

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5 · Trust

Company site · found 29 Sep 2026
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They ask for

Experience not statedNo degreeMachine learning

Full description

Shown as posted, in English

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 https://terac.com/interview/start/r/8b2a6e81-53d0-408e-b498-8fc46a15fdee?utm_source=ashby_listing_description   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 https://terac.com or on YouTube at @jointerac https://www.youtube.com/@jointerac.

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GigTerac · company sitePosted 3 weeks ago

Machine Learning Engineers: Scenario Building for Reinforcement Learning

1 · Can you apply from United States?

Open to United States
United StatesExact words from the ad · found 29 Sep 2026

4 · Your working hours

Not stated

The ad doesn’t say which hours. Ask the company.

5 · Trust

Company siteFound 29 Sep 2026
No one should ask you to pay to work.
Something wrong?Report this post

They ask for

Experience not statedNo degreeMachine learning

Full description

Shown as posted, in English

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 https://terac.com/interview/start/r/8b2a6e81-53d0-408e-b498-8fc46a15fdee?utm_source=ashby_listing_description   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 https://terac.com or on YouTube at @jointerac https://www.youtube.com/@jointerac.