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Top GitHub Contributors – Agentic Review Project

STEP 1 · PRACTICE FIRSTTake a free AI practice interview for this kind of roleGet my practice interview ↓
STEP 2 · APPLYApply on Turing when you’re readyApply on Turing →

You apply directly on Turing's site. Applying is free. Posted Mar 13, 2026.

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STEP 1 · PRACTICE BEFORE YOUR REAL INTERVIEW

Get your free practice interview for this role

Turing screens applicants online, often with an AI interview. micro1 offers a free, 18-minute AI practice interview with feedback, and we picked the one closest to this role: Data Annotator. It covers:

Instruction FollowingAttention to DetailLogical Reasoning

Here’s your practice interview

Allow your microphone when it asks, find a quiet spot, and give yourself about 20 minutes. We’ve also emailed you the link and the free ebook.

Step 2: when you feel ready, apply.

Apply on Turing →

The practice interview is free and run by micro1. Land Remote Jobs is an independent job board, not part of micro1, Mercor or Turing. Practising helps you prepare; it can’t guarantee the result of your real interview. Want more tips? Read our guide to acing the remote job interview.

STEP 2 · APPLY

Apply for this role

You apply on Turing's own site. It’s free, and you can apply even if you skip the practice.

Apply on Turing →

Who this role suits

Working engineers who want flexible, project-based remote work that uses their coding and review skills. A strong portfolio or GitHub helps.

Rust

Full job description

About Us
Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in software engineering, logical reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.

Project Overview
We are seeking high-caliber researchers and technical experts. The core objective of this role is to enhance the reasoning and problem-solving capabilities of a target frontier model by designing, validating, and analyzing challenging benchmark tasks.

What the role entails:

  • Task Design and Development: Design challenging, real-world problems that serve as the foundation for a model. Problems should be constructed to target specific core capability loss failures identified in a leading model.
  • Content Generation: Integrate the problems into an Agentic development environment, preparing all necessary components using Python, which include:
    • Detailed Instructions and an overview of the required task.
    • A Golden solution that follows the instructions.
    • The necessary Environment, including datasets, Python libraries, and metadata.
    • A Test notebook containing unit tests that solutions must pass.
  • Evaluation and Analysis: Evaluate the cross model’s performance on the tasks.
  • Headroom Identification: Identify tasks where target model fails to pass all tests, specifically classifying the failure as a logical reasoning failure.
  • Loss Extraction: Analyze the agent’s steps (Agent Trajectory) to observe and extract core capability loss patterns from the model.

Required Skills

  • Highly-skilled GitHub contributors.
  • Applicants must have strong expertise in either data science, ML, coding, or a deep quantitative background in frontier STEM.
  • Able to engage reliably for 30+ hrs per week (on weekdays).

Evaluation Process

  • The application process takes ~15 minutes.
  • Completion of an AI video interview is required.

Last checked open on Nov 6, 2026. Job description provided by Turing.

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