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Machine Learning Evaluation Specialist (Remote)

Roles & Responsibilities

  • Graduate-level expertise (MS or PhD preferred) in a scientific or technical domain that intersects with ML.
  • Strong working knowledge of ML methods, including model selection, feature engineering, and evaluation metrics.
  • Deep familiarity with active research problems in your field and the ability to identify where general ML knowledge falls short.
  • Excellent written communication and independent, self-motivated work on intellectually demanding tasks.

Requirements:

  • Propose and frame original, research-grade ML problems rooted in your domain.
  • Design evaluation tasks that require specialized knowledge well beyond standard pipelines.
  • Assess AI-generated solutions for correctness, creativity, and methodological rigor, and explain exactly where and why they fall short.
  • Document problem difficulty, required domain knowledge, and expected failure modes.

Job description

Machine Learning Evaluation Specialist (Remote)

List of accepted countries and locations

Important for US applicants: This is a 1099 independent contractor role and is not compatible with F-1 OPT, STEM OPT, or other visa statuses that require W-2 employment, guaranteed hours, or employer sponsorship. We are unable to provide offer letters or employment verification for this role.

Help design the hardest ML problems state-of-the-art AI hasn't solved yet.

We're hiring domain experts to build evaluation tasks that challenge the frontier of AI. This is not an ML engineering role — it's a research role. You'll use deep expertise in your field to create problems that general ML knowledge can't touch.

What you'll do

  • Propose and frame original, research-grade ML problems rooted in your domain

  • Design evaluation tasks that require specialized knowledge well beyond standard pipelines

  • Assess AI-generated solutions for correctness, creativity, and methodological rigor — and explain exactly where and why they fall short

  • Document problem difficulty, required domain knowledge, and expected failure modes

What you need

  • Graduate-level expertise (MS or PhD preferred) in a scientific or technical domain that intersects with ML

  • Strong working knowledge of ML methods — model selection, feature engineering, evaluation metrics

  • Deep familiarity with active research problems in your field — you know where general ML knowledge runs out

  • Excellent written communication — you can articulate complex problems clearly and precisely. This cannot be overstated.

  • Self-motivated and comfortable working independently on intellectually demanding tasks

What you don't need

  • No prior AI training or RLHF experience required

  • No software engineering background needed — domain expertise and research instincts are what matter

Domains we're especially looking for

  • Computational Biology / Bioinformatics

  • Genomics / Molecular Biology

  • Physics / Astrophysics / Signal Processing

  • Climate / Environmental Modeling

  • Healthcare / Medical Imaging

  • Neuroscience / Brain-Computer Interfaces

  • Materials Science / Chemistry

  • Finance / Quantitative Modeling

  • Robotics / Control Systems / Reinforcement Learning

  • Advanced NLP (specialized domains)

  • Mathematics / Statistics (applied)

Logistics

  • Fully remote — work from anywhere

  • $200–$400/hr depending on domain and seniority

  • 10–40 hrs/week, hourly contract

  • Assessment required — paid if approved

  • Independent contractor (1099) — not compatible with F-1 OPT, STEM OPT, or visa statuses requiring W-2 employment or employer sponsorship

⚠️ This is a project-based, freelance opportunity with no guaranteed hours. We recommend keeping other work options open while waiting for project assignment.

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