$70-$180/hr chemistry and materials science work, on your schedule
Review AI-generated syntheses, mechanisms, and chemical analyses the way you'd review a route before running it. Flag the step that won't proceed, the mechanism that's drawn wrong, the hazard a model ignores. The intuition for what actually happens in the flask - not just on paper - is exactly what AI labs need.
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Hi, we're Zac and Jack, the founders of Terac. We want to talk to you directly, because you are the most important part of what we're building.
Terac is a community of experts. People who have spent years getting good at something specific and hard. The world is about to need more of you, not less. As AI takes on more of the world's work, the bottleneck shifts to the people who actually know what they're talking about.
Expert labor is the rarest resource in the world right now, and it is shockingly hard to find. The companies that need a chemist's eye on a synthesis route that won't work spend weeks chasing people, paying placement fees, and settling for whoever is available. Meanwhile thousands of qualified people are sitting with knowledge that no one ever asks for.
That gap is what we're here to close. Every project that lands on Terac is routed to the people who actually know the answer, on their schedule, paid fairly, and only when the work is verified. No middleman taking a cut of your time. No vague gigs. No chasing checks.
We care about every single person in this community. If you join Terac, you're not a row in a database to us. We read the feedback. We answer the emails. We will fight for you when a customer is being unreasonable, and we will be honest with you when something on our side is broken. The quality of this panel is our entire company, and we owe you a serious bar.
If you've made it this far, here is what we're asking: claim your profile. Put your expertise on the record. Let the world's most ambitious teams come find you for the work only you can do.
Chemistry questions
Still curious? Write to us at support@terac.com.
Niche sub-specialties are often the most valuable, because frontier AI models struggle most with expert-level reasoning in narrow domains where training data is sparse. Whether your background is in ligand design, density functional theory, polymer rheology, or asymmetric catalysis, the work is to evaluate how well a model reasons within that specific corner of the field, not to cover chemistry broadly.
Yes, regulatory and safety credentials qualify for tasks that involve reviewing AI outputs on chemical handling, EHS compliance, GHS labeling, or OSHA Process Safety Management. The credential that matters is the one that makes you a domain authority on the specific output you are evaluating, so a CCHO is exactly right for reviewing AI-generated safety data sheet language or chemical hygiene plan text.
Terac does not assign tasks that involve generating or validating novel synthesis routes for controlled precursors, select agents, or materials with clear weapons-relevant applications. If a task touches a sensitive area, you can decline it without penalty, and the platform will not ask you to override your professional judgment about what is appropriate to engage with.
Typical deliverables include annotating AI-written mechanistic explanations for accuracy, scoring model-generated spectral interpretations (NMR, IR, mass spec) against the correct reasoning a trained chemist would apply, writing worked examples that show step-by-step retrosynthetic analysis or kinetic derivations, and flagging errors in AI responses about reaction conditions, stoichiometry, or thermodynamic feasibility. The work draws on the same technical judgment you use day-to-day, not on writing or communication skills.
Yes. Tasks are designed around publicly documented chemistry, standard literature methods, and general domain knowledge, so you will never be asked to reproduce, describe, or validate anything derived from a proprietary internal system or trade-secret process. Your value is your trained expert judgment on how AI reasons about chemistry, which you have entirely independent of any employer-specific information.
Why your expertise matters
Chemistry sits at the core of drug discovery, materials science, and environmental safety, and AI models that reason over reaction mechanisms, spectral data, or synthesis routes make consequential errors that only a trained chemist can catch. Incorrect stereochemistry assignments, plausible-but-wrong retrosynthetic disconnections, and misinterpreted NMR splitting patterns are invisible to a generalist reviewer but immediately obvious to someone who has spent time at the bench. Your field-specific judgment is what converts a fluent-sounding model output into something that is actually chemically valid.
How pay works
Pay within the $70-$180/hr band scales with depth of specialization: a synthetic organic chemist who can evaluate multi-step route feasibility or interpret 2D NMR data commands more than a generalist, and PhDs or industry veterans with regulatory or GMP experience frequently land at the upper end. All work is fully remote, billed by the verified hour or by the completed task, and payment releases only after your submission is confirmed - no speculative hours, no retainer.
What the work looks like
A sample of the chemistry and materials science work you would pick up. Every project is scoped, remote, and paid on verified completion.
- Review an AI-generated synthetic route for a target molecule, identifying steps where the proposed reagents would cause competing reactions, selectivity failures, or safety hazards that the model did not flag.
- Evaluate a set of AI-predicted NMR spectra against a proposed structure and annotate where the chemical shift assignments or coupling constants are inconsistent with the actual molecular environment.
- Write a step-by-step worked example of a retrosynthetic disconnection for a polycyclic natural product, showing the expert reasoning behind each strategic bond disconnection so the model can learn from it.
- Assess an AI answer about reaction mechanisms for accuracy, checking whether electron-pushing arrows, intermediate stability, and stereochemical outcomes are correctly described.
- Label a batch of AI-generated SDS summaries for accuracy and regulatory compliance, flagging where hazard classifications deviate from GHS criteria or where exposure limits are incorrectly cited.
- Create a set of comparative reaction scenarios - for example, Mitsunobu versus Appel conditions for a specific substrate - that test whether a model correctly predicts chemoselectivity differences based on functional group compatibility.
Specialties we match
Chemistry projects span a wide range of focus areas. Tell us where you go deep and we route the work that fits.
- Synthetic organic chemistry
- NMR spectroscopy interpretation
- Retrosynthetic analysis
- Computational chemistry (DFT/MM)
- Medicinal chemistry / SAR
- Analytical chemistry (HPLC, LC-MS, GC-MS)
- Process chemistry and scale-up
- Green chemistry and solvent selection
- Polymer and materials chemistry
- Regulatory chemistry (ICH, EPA, REACH)
- Electrochemistry and battery materials
- Biochemistry and enzyme kinetics
