AI Research

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🔥 1 hour ago

🌏 Anywhere in the World

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧠 AI Research Scientist

👻 Ghost score 15%

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Vetto AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

Artificial Intelligence • SaaS • 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.

📋 Description

• Design and run experiments to understand model behavior, test ideas, and evaluate datasets or training interventions • Use fine-tuning and post-training experiments to validate research hypotheses and measure capability improvements • Create datasets, benchmarks, agent environments, rubrics, and evaluation methods • Work with AI labs and enterprise partners to turn model-development goals into research and data projects • Analyze model outputs and trajectories to identify systematic failure modes and distinguish model, data, grader, and evaluation issues • Write analysis code and build lightweight tools or prototypes, with engineering support for reliable infrastructure • Share findings through technical reports, internal discussions, benchmarks, and research papers • Report to the co-founders

🎯 Requirements

• Experience doing empirical research or similarly open-ended technical work with machine learning systems • Hands-on experience designing and running agentic systems for complex work, such as coding agents and automated research pipelines • Good experimental judgment, including hypothesis formation, baseline and metric selection, careful experimentation, and interpretation of noisy results • Strong Python and data analysis skills • Sufficient software engineering ability to prototype research workflows • Independence in turning ambiguous model questions into datasets, benchmarks, experiments, or other concrete contributions • Rigorous analytical thinking and ability to identify subtle failure modes • Excellent written and verbal communication with researchers, engineers, customers, and non-specialists • Comfort with ambiguity, fast iteration, changing priorities, and occasional forward-deployed work with partner teams • Graduate degree, publications, lab experience, open-source work, independent research, and production engineering experience are useful signals but none is required on its own

🏖️ Benefits

• Competitive compensation and a stock option plan • Global, remote-first work with flexibility • Periodic in-person on-sites every few months • Direct collaboration with cutting-edge AI labs on evaluation, data, and post-training challenges • High ownership and fast career growth in a founding-era team

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