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Careerflow.ai

AI/ML Software Engineer (RL Environments) (Contract)

Reposted 8 Days Ago
Remote
Hiring Remotely in IN
Mid level
Remote
Hiring Remotely in IN
Mid level
Design and build reinforcement-learning training environments and diverse tasks to evaluate and improve LLM agents; iterate rapidly on task designs from customer feedback, deliver high-quality outputs with minimal supervision, and maintain PST overlap for collaboration.
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About the Role

We're seeking experienced Machine Learning Engineers and Software Engineers with ML experience to design and build high-quality RL training environments for LLM agents. As an RL Environment Engineer, you'll create diverse machine learning tasks that challenge and improve language models, working with minimal supervision to deliver consistent, quality outputs.

What You'll Do
  • Design and build tasks for machine learning domains that target specific language models and difficulty distributions

  • Iterate rapidly on task designs based on customer feedback, with 24-hour turnaround times

  • Create diverse, challenging scenarios that test language model capabilities and expose their limitations

  • Hit the ground running with minimal onboarding time

What We're Looking For
  • Strong machine learning background through coursework, previous work experience, or personal projects

  • Python fluency: you write clean, efficient Python code regularly

  • Heavy LLM user who understands current model capabilities and failure modes through daily hands-on experience

  • Self-directed and creative. You can generate novel ML task ideas in your domain without constant guidance

  • High responsibility and integrity. You deliver quality work consistently and meet deadlines

  • Availability overlap with PST 9am-5pm (minimum 3 hours required)

Work Details
  • Location: Remote

  • Type: Contractor

Time Commitment: 40 hours a week. Must have at least 3 hours of overlap with PST business hours (9am-5pm)

Selection Process:
  1. Screening

  2. Hacker rank assessment

  3. 1 Week paid task

  4. Full time

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