Data Scientist
Tonic AI · Artificial Intelligence
unknown
Salary Range (USD)
Negotiable
Location
Location N/A
Visa Support
Not mentioned
Funding Stage
Unknown
Job Responsibilities
- • Design and build 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
- • Train and improve NER models behind entity detection, driving accuracy and recall across free text, structured fields, and mixed enterprise data at scale
- • Build evaluation infrastructure that grades agent outcomes and produces real discrimination between frontier models on real tasks
- • Fine‑tune and evaluate open‑weight models on Tonic‑generated data, turning benchmark results into product and research direction
- • Expand coverage into new domains, languages, and entity types, handling long‑tail formats and edge cases
- • Own model evaluation across precision/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 teams 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
Required Skills
Machine LearningData ScienceNatural Language ProcessingSynthetic Data GenerationModel EvaluationInference Optimization
Engineering Culture & Tech Stack
ownership
leadership
product‑minded
research collaboration
rigorous
reproducibility
Raw Post
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Tonic AI (https://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 work with frontier AI labs pushing the edge of what models can do, and with hundreds of enterprises including Fidelity, Comcast, eBay, and Vanguard, on the data problems that sit at the center of where AI is going next.
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-b62... but also shoot me an email at adam + (company domain name).
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