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