Biochemist

Job summary

Create challenging biochemistry problems and precise, step-by-step solutions to benchmark advanced AI systems. Review AI-generated scientific content for accuracy, validity, and safety, then document reasoning errors and provide structured feedback to improve model performance.

Job details

Biochemist – AI Data Trainer About The Role We're looking for PhD-level Biochemists to help train and refine some of the most advanced AI models in the world. Your deep scientific expertise will directly shape how AI reasons about protein folding, metabolic pathways, molecular genetics, and enzyme kinetics — making a real impact on the future of AI in life sciences. This is a fully remote, flexible contract role. No prior AI experience required. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design Challenging Problems — Create advanced biochemistry problems spanning nucleic acid chemistry, proteomics, structural biology, and drug-target interactions to rigorously test AI performance. Author Gold-Standard Solutions — Write precise, step-by-step technical solutions that serve as benchmarks for high-level scientific reasoning in AI systems. Audit AI Outputs — Evaluate AI-generated biochemical pathways, molecular structures, and mathematical proofs for technical accuracy, scientific validity, and safety. Refine AI Reasoning — Identify and document logical errors in AI reasoning — such as incorrect stoichiometry, flawed stereochemistry, or misapplied kinetics — and provide structured feedback to improve model performance. Who You Are Holds a PhD (completed or near completion) in Biochemistry, Molecular Biology, or a closely related field Deep domain knowledge in areas such as structural biology, enzymology, cellular metabolism, or bioinformatics Able to communicate complex biochemical and chemical concepts clearly and precisely in written form Highly detail-oriented when reviewing chemical equations, molecular diagrams, and experimental protocols Self-motivated and comfortable working independently and asynchronously No prior AI or machine learning experience required Nice to Have Experience with data annotation, data quality, or evaluation workflows Familiarity with computational biochemistry tools such as PyMOL, AlphaFold, or BLAST Background in scientific writing, peer review, or technical communication Why Join Us Work on cutting-edge AI projects alongside world-leading research labs Fully remote and flexible — work on your own schedule Freelance perks: autonomy, variety, and global collaboration Gain meaningful exposure to how advanced large language models are trained and evaluated Contribute to work that shapes how AI understands and communicates science Potential for ongoing work and contract extension

What you’ll do

Create challenging biochemistry problems and precise, step-by-step solutions to benchmark advanced AI systems. Review AI-generated scientific content for accuracy, validity, and safety, then document reasoning errors and provide structured feedback to improve model performance.

Requirements

Applicants must hold a completed or nearly completed PhD in biochemistry, molecular biology, or a closely related field, with deep expertise in relevant biochemical disciplines. They must communicate complex concepts clearly, review technical material carefully, and work independently; prior AI experience is not required.

Benefits

• Flexible Schedule
• Remote Work
• Autonomy
• Global Collaboration
• Potential Contract Extension

Listed skills

• Accuracy · Preferred
• safety · Preferred
• Technical · Preferred
• Flexible · Preferred
• Collaboration · Preferred
• Audit · Preferred
• Communication · Preferred
• Detail-oriented · Preferred
• future · Preferred
• Machine learning · Preferred
• Organization · Preferred
• Évaluation · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Biochemistry
• Molecular Biology
• Structural Biology
• Enzymology
• Cellular Metabolism
• Bioinformatics
• Protein Folding
• Metabolic Pathways
• Molecular Genetics
• Enzyme Kinetics
• Proteomics
• Nucleic Acid Chemistry
• Drug-Target Interactions
• Scientific Writing
• Data Annotation
• AI Output Evaluation

Job areas

• Science & Research
• Technology
• Data & Analytics

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