Chemistry Masters — AI Data Trainer

About The Role

We're looking for chemistry experts to help train and improve the next generation of AI models. At Alignerr, we partner with the world's leading AI research labs — and we need people who truly understand chemistry to help AI think more rigorously about it.

If you have a Master's in Chemistry, Chemical Engineering, Biochemistry, or a related field, this is a rare opportunity to apply your deep domain knowledge in a high-impact, fully remote role — on your own schedule.

No AI Experience Required.

Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week

What You'll Do

Design advanced chemistry problems to rigorously test AI reasoning and performance across domains like chemical engineering, biochemistry, thermodynamics, and more Develop clear, detailed, step-by-step solutions that demonstrate rigorous scientific logic Evaluate AI-generated responses for accuracy, depth, and quality of reasoning Collaborate with researchers to refine and improve benchmarks spanning undergraduate through Master's-level chemistry Provide structured, high-quality feedback that directly shapes how AI systems understand science

Who You Are

Currently pursuing or have completed a Master's degree in Chemistry, Chemical Engineering, Biochemistry, or a closely related field Strong analytical and problem-solving skills across advanced chemistry domains Able to communicate complex scientific concepts clearly and precisely in writing Self-motivated, detail-oriented, and comfortable working independently No prior AI or data annotation experience required

Nice to Have

Experience with data annotation, data quality evaluation, or research benchmarking Familiarity with large language models or AI evaluation workflows Background spanning multiple chemistry sub-disciplines

Why Join Us

Work on cutting-edge AI projects alongside the world's top research labs Fully remote and asynchronous — work from anywhere, on your own schedule Freelance perks: autonomy, flexibility, and the ability to scale hours up or down Direct impact on how AI systems reason through complex scientific problems Potential for ongoing work and contract renewals