Machine Learning Evaluation Specialist (Remote)

This listing is synced directly from the company ATS.

Role Overview

This senior-level research role involves designing and evaluating complex machine learning problems that challenge state-of-the-art AI, requiring deep domain expertise. Day-to-day tasks include proposing original ML problems, creating specialized evaluation tasks, and assessing AI-generated solutions for correctness and rigor. The hire will work independently on intellectually demanding projects, impacting the frontier of AI research by identifying and documenting failure modes in advanced domains.

Perks & Benefits

The role offers fully remote work from anywhere with flexible hours of 10–40 per week, ideal for independent contractors. Compensation is high at $200–$400 per hour, depending on domain and seniority, and includes paid assessments if approved. It provides a project-based, freelance opportunity with no guaranteed hours, suitable for self-motivated professionals seeking intellectually challenging work in a research-focused environment.

Full 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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