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This position was posted on April 13, 2026 and is likely no longer accepting applications. We've kept it here for historical reference. Check out the similar jobs below!

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Machine Learning Evaluation Specialist - Remote

Job Overview

Location

Austin

Job Type

Contract

Category

Data Science

Date Posted

April 13, 2026

Full Job Description

đź“‹ Description

  • • As a Machine Learning Evaluation Specialist, you will design research-grade evaluation tasks that push the boundaries of current AI capabilities by creating problems that state-of-the-art models cannot solve using standard approaches.
  • • Your day-to-day work involves proposing original ML problems grounded in your domain expertise, designing evaluation tasks requiring specialized knowledge beyond typical pipelines, assessing AI-generated solutions for correctness and creativity, and documenting where and why models fail.
  • • You will join a remote-first team at G2i Inc. focused on advancing AI safety and capability through rigorous, domain-specific benchmarking, collaborating with experts across scientific and technical fields.
  • • In this role, you will deepen your impact as a domain expert by shaping how AI is evaluated, publishing implicitly through task design, and contributing to the frontier of ML research without needing to build models or write production code.

Skills & Technologies

Remote
$200-400/hr
Degree Required

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About G2i Inc.

G2i is a technical talent marketplace that pre-vets React, React Native, and Node.js engineers for U.S. companies. Founded by developers to solve hiring pain, it runs extensive code reviews, pair-programming interviews, and background checks before matching engineers for contract or full-time remote roles. G2i emphasizes mental health, offering a monthly wellness stipend and a zero-burnout policy. The company also provides direct-hire services and manages payroll, compliance, and ongoing support, enabling startups and enterprises to scale engineering teams quickly while maintaining code quality and developer well-being.

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