Chemistry Specialist

$70–90/hrrate as listed

micro1 is contracting chemists to write, review, and stress-test technical content used to train and evaluate AI models on chemical reasoning. Work is remote and contract-based, with observed rates in the $70–90/hr range depending on depth of experience and project.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

What the work involves

You write and grade chemistry at the level you'd expect from a graduate seminar or a methods section. Typical tasks include constructing problems that require multi-step reasoning across synthesis, mechanism, or analytical interpretation; writing reference answers with the working shown; comparing two model responses and explaining precisely where one fails; and rewriting model output that is fluent but chemically wrong. Some projects lean toward spectral and chromatographic interpretation, others toward reaction design, stoichiometry, thermodynamics, or lab methodology and safety reasoning.

The hardest part is usually not the chemistry — it's the specificity of the critique. A note saying "incorrect mechanism" is not usable; a note identifying that the model invoked an SN2 pathway at a tertiary center, then propagated the error into the wrong stereochemical outcome, is. Reviewers are held to written rubrics, and consistency across a batch matters as much as correctness on any single item.

What the platform screens for

micro1 runs an AI-led interview before human review. Expect follow-up questions that push past your first answer: if you name a technique, you'll be asked about its limits, failure modes, and what you'd do when it doesn't work. The screen is looking for verifiable specifics — instruments you've actually run, reactions you've actually troubleshot, papers or theses you can point to — rather than general familiarity. An advanced degree (PhD preferred) in chemistry or a closely adjacent field is the baseline expectation, along with substantial hands-on wet lab time. No AI or ML background is required.

Logistics

Fully remote, contractor engagement, invoiced hourly
Largely asynchronous; work is pulled from a queue rather than scheduled in meetings
Projects commonly ask for 10–20+ hours per week, with volume that fluctuates by customer demand
Rates in the $70–90/hr band are as observed on this listing and vary by project, seniority, and task type — treat them as indicative, not guaranteed
Expect a calibration period with sample tasks and reviewer feedback before full task access

What they look for

Chemistry
Wet Labs
Critical Thinking
Chemical Reactions

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you hold a PhD, MS, or equivalent advanced degree (e.g., postdoctoral qualification) in Chemistry, Biochemistry, Chemical Engineering, Analytical Chemistry, or a closely related discipline?
Advanced degree in Chemistry or related field · preferred
Have you conducted hands-on laboratory experiments and chemical analyses in an academic, industrial, or research setting for at least 2 years?
Hands-on wet lab experience · required
Are you able to communicate technical concepts clearly in written English (for documentation and reports) and verbal English (for collaboration)?
English fluency (written and verbal) · required
Do you have reliable internet access and a suitable workspace to work remotely as a contractor?
Remote work capability · required

0 of 4 answered

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Whether candidate can articulate experimental logic, isolate variables, and adapt when outcomes diverge—core to designing rigorous lab work and training AI on realistic scientific reasoning.
A strong answer: Describe a specific synthesis or analysis with a clear objective, explain the method chosen and why, identify what went wrong or was unexpected, and explain the diagnostic steps taken to understand the discrepancy and validate the corrected approach.
Where people lose it: Skipping the troubleshooting part or treating unexpected results as a failure rather than a learning moment; candidates who cannot articulate *how* they debugged experiments signal weak experimental thinking.