Tonic AI ( builds the data infrastructure behind modern AI. We generate the synthetic environments that agents are trained and tested in, and we de-identify real enterprise data so it can be used safely in training and evaluation. Eight years in, we wo...
HN Hiring Remote
Why this grade
This listing scored 37/100, which is an F. It lost the most ground on pay transparency.
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Remote clarity 15 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Freshness 4 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Role specificity 3 / 10 Whether the listing is tagged well enough to tell what the role actually is.
- Pay transparency 0 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
-10 Ghost-job penalty — Deducted for signals that this posting may not be a real, currently-open role — staleness, repeated relisting, or talent-pool language.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
hn-hiring
We are looking for a data scientist with 8+ years experience (or 3+ with relevant PHD). In this role you will:
++ Design and build the systems that generate longitudinally coherent synthetic environments for agent training and evaluation, including persona modeling, task generators, and verifiable ground truth.
++ Build and maintain synthesis models that generate realistic replacement values at very large scale, preserving format, statistical distribution, and semantic consistency so de-identified data stays useful downstream.
++ Train and improve the NER models behind our entity detection, driving accuracy and recall across free text, structured fields, and mixed enterprise data at scale.
++ Build evaluation infrastructure that grades agent outcomes, not just traces, and produces real discrimination between frontier models on real tasks.
++ Fine-tune and evaluate open-weight models on Tonic-generated data, and turn benchmark results into product and research direction.
++ Expand coverage into new domains, languages, and entity types, and handle the long tail of formats and edge cases that real customer data throws off.
++ Own model evaluation across the board: precision and recall on detection, utility preservation on synthesis, and outcome-level grading for agents.
++ Optimize inference so models run efficiently on large volumes of sensitive data inside customer environments.
++ Partner directly with frontier labs and enterprise ML team to turn hard data problems into shipped model improvements.
++ Set technical direction for a small, senior team and raise the bar on rigor, reproducibility, and shipping.
Apply here: https://jobs.ashbyhq.com/TonicAI/048a114d-fb5f-46ef-b0ff-b62365ff5fc2 but also shoot me an email at adam + (company domain name).
Apply for this role Opens tonic.ai — the link as listed; we have not yet verified it is the employer's own page