
11 - 50 employees
Founded 2022
đ€ Artificial Intelligence
âïž SaaS
đą Enterprise
Artificial Intelligence âą SaaS âą Enterprise
Vetto AI is a company that designs learning experiences, feedback systems, and evaluation frameworks to improve real-world capabilities of machine learning models. They provide data, benchmarks, leaderboards, research, and enterprise products aimed at shaping how models learn and how experience reaches models, and are used by frontier AI labs. Vetto focuses on creating tasks, evaluations, and data pipelines that directly improve model performance and developer workflows.
đ„ 15 minutes ago
đ Anywhere in the World
â° Full Time
đĄ Mid-level
đ Senior
đ§ AI Research Scientist
đ» Ghost score 15%
Where this job comes from
Posted on Vetto AI's careers page, not through a job board
First seen by Remote Rocketship 15 minutes ago

11 - 50 employees
Founded 2022
đ€ Artificial Intelligence
âïž SaaS
đą Enterprise
Artificial Intelligence âą SaaS âą Enterprise
Vetto AI is a company that designs learning experiences, feedback systems, and evaluation frameworks to improve real-world capabilities of machine learning models. They provide data, benchmarks, leaderboards, research, and enterprise products aimed at shaping how models learn and how experience reaches models, and are used by frontier AI labs. Vetto focuses on creating tasks, evaluations, and data pipelines that directly improve model performance and developer workflows.
âą Design and run experiments to understand model behavior, test ideas, and evaluate datasets or training interventions âą Use fine-tuning and post-training experiments to validate research hypotheses and measure capability improvements âą Create datasets, benchmarks, agent environments, rubrics, and evaluation methods âą Work with AI labs and enterprise partners to turn model-development goals into research and data projects âą Analyze model outputs and trajectories to identify systematic failure modes and distinguish model, data, grader, and evaluation issues âą Write analysis code and build lightweight tools or prototypes, with engineering support for reliable infrastructure âą Share findings through technical reports, internal discussions, benchmarks, and research papers âą Report to the co-founders
âą Experience doing empirical research or similarly open-ended technical work with machine learning systems âą Hands-on experience designing and running agentic systems for complex work, such as coding agents and automated research pipelines âą Good experimental judgment, including hypothesis formation, baseline and metric selection, careful experimentation, and interpretation of noisy results âą Strong Python and data analysis skills âą Sufficient software engineering ability to prototype research workflows âą Independence in turning ambiguous model questions into datasets, benchmarks, experiments, or other concrete contributions âą Rigorous analytical thinking and ability to identify subtle failure modes âą Excellent written and verbal communication with researchers, engineers, customers, and non-specialists âą Comfort with ambiguity, fast iteration, changing priorities, and occasional forward-deployed work with partner teams âą Graduate degree, publications, lab experience, open-source work, independent research, and production engineering experience are useful signals but none is required on its own
âą Competitive compensation and a stock option plan âą Global, remote-first work with flexibility âą Periodic in-person on-sites every few months âą Direct collaboration with cutting-edge AI labs on evaluation, data, and post-training challenges âą High ownership and fast career growth in a founding-era team
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