Work Expert (WE) is an independent publishing and referral website. We are not a recruiter, hiring manager, agent or employer, and we are not affiliated with or endorsed by Mercor. Applying takes you to the platform's own website, where we may be recorded as the referring source. We may receive a referral fee at no additional cost to you. Read our full affiliate disclosure →
About the Role
This is a full-time W-2 opportunity with Cincinnatus LLC. As part of this role, you may be staffed as a contractor with a leading technology company. Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced AI models.
What You'll Do
Design tasks: Turn real ML research ideas - like tweaking how an RL reward is computed - into well-defined, multi-step tasks.
Run experiments: Implement changes, run training experiments, and analyze the results to show what a correct solution looks like.
Explore RL ideas: Build some of your tasks around reinforcement-learning basics such as reward functions and training behavior.
Evaluate models: See how frontier models handle your tasks, and note where and why they fall short.
Independent contractor engagement, fully remote. Mercor pays weekly via Stripe or Wise.
Common Questions
Mercor has a reliability rating of very reliable based on the listings we track, with an onboarding time of 1-3 weeks (interview + assessment + trial). See our full Mercor review for the details behind that rating.
Applying takes you to Mercor's own website, where the application is completed. We are not a recruiter or employer and do not process applications directly - we may be recorded as the referring source.
$60-$90/h - Independent contractor engagement, fully remote. Mercor pays weekly via Stripe or Wise.
Design tasks: Turn real ML research ideas - like tweaking how an RL reward is computed - into well-defined, multi-step tasks. Run experiments: Implement changes, run training experiments, and analyze the results to show what a correct solution looks like. Explore RL ideas: Build some of your tasks around reinforcement-learning basics such as reward functions and training behavior.
