Analytical Chemist
We’re building experimentally verified chemistry datasets to help AI models reason more accurately about molecules and chemical structures.
We’re looking for an analytical chemist to produce the measurements those datasets depend on: clean, well-documented NMR and mass-spectrometry data that we can trust as ground truth.
What you’ll do
- Prepare samples and acquire 1D and 2D NMR (¹H, ¹³C, COSY, HSQC, HMBC), LC-MS and HRMS data at partner laboratories and instrument facilities.
- Process raw data (FIDs, chromatograms, mass spectra) and export it in consistent, well-labelled formats.
- Check every dataset for quality: shimming, referencing, solvent and impurity peaks, mass calibration, adducts and carry-over.
- Record full measurement metadata: instrument, solvent, method and conditions.
- Flag spectra that don’t fit the proposed structure, and work with our R&D chemist to resolve them.
- Help build simple, repeatable procedures so that measurements from different labs are comparable.
What we’re looking for
- A BSc or MSc in chemistry, with hands-on experience running NMR, LC-MS or HRMS instruments.
- Confident data processing in tools such as MestReNova, TopSpin, MassLynx, Xcalibur or similar.
- Careful, systematic work and clear documentation.
- Enough structural chemistry to spot when data and structure don’t agree.
Good to have
Experience in a CRO, QC or analytical-services lab, or an NMR or mass-spectrometry facility; method development; familiarity with Python or RDKit. Prior AI experience is optional.
Why join
Your measurements become the ground truth AI models are trained and tested against. You’ll work directly with the founders and help set the standard for verified chemistry data.
Commitment and compensation
Initial commitment, salary and equity will be discussed transparently. We’re open to an initial part-time collaboration, with a planned transition to full-time after funding.
To apply
Share your CV and one example of a measurement problem you solved: a spectrum or chromatogram that looked wrong, how you found the cause, and how you fixed it.