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About the role
Key responsibilities & impact- 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
Requirements
What you’ll 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
Benefits
Comp & perks- Fully remote — work from anywhere
- Assessment required — paid if approved
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learning methodsmodel selectionfeature engineeringevaluation metrics
Soft Skills
written communicationself-motivatedindependent workarticulation of complex problems
Certifications
MSPhD