Biochemistry AI Training Specialist (Remote, Flexible)

Alignerr Corp.; United States; Remote; AUD 83,000 - 165,000; Full time

Job summary

Alignerr Corp. seeks a Biochemistry Subject Matter Expert (AI Training) for a fully remote hourly contract. PhD-level biochemists with deep domain knowledge are invited to apply, 10–40 hours/week.

You will design advanced problems across nucleic acid chemistry, proteomics, structural biology, and drug-target interactions to stress-test AI performance; author gold-standard solutions; audit AI outputs; and identify reasoning failures to guide model improvements.

Qualifications

• PhD-level Biochemists to help train and refine AI models.
• PhD completed or in progress in Biochemistry, Molecular Biology, or related field.
• Deep domain knowledge in structural biology, enzymology, cellular metabolism, bioinformatics, or related disciplines.
• Clear technical communicator with precision and clarity in written form.

Responsibilities

• Design Advanced Problems — Create challenging biochemistry problems across domains like nucleic acid chemistry, proteomics, structural biology, and drug-target interactions to stress-test AI performance
• Author Ground-Truth Solutions — Write precise, step-by-step technical solutions that serve as gold-standard benchmarks for AI scientific reasoning
• Audit AI Outputs — Evaluate AI-generated biochemical pathways, molecular structures, and mathematical derivations for technical accuracy
• Identify Reasoning Failures — Spot logical errors in AI reasoning and provide structured feedback to improve model performance

Skills

Biochemistry expertise

Scientific communication

Attention to detail

Education

PhD in Biochemistry/Molecular Biology

Tools

PyMOL

AlphaFold

BLAST

Job description

Alignerr Corp. seeks a Biochemistry Subject Matter Expert (AI Training) for a fully remote hourly contract. PhD-level biochemists with deep domain knowledge are invited to apply, 10–40 hours/week.

You will design advanced problems across nucleic acid chemistry, proteomics, structural biology, and drug-target interactions to stress-test AI performance; author gold-standard solutions; audit AI outputs; and identify reasoning failures to guide model improvements.