Research Scientist, Applied AI

Agentio builds AI-native infrastructure for creator advertising. Our platform uses AI to turn creative and performance signals into campaign strategies, match brands with creators, recommend sponsorship prices, and review videos against brand requirements.

Each campaign generates feedback: how brands respond to our recommendations, which offers creators accept, and how the resulting content performs. We build self improving loops that learn from these behaviors and outcomes to better understand preferences, predict performance, and improve campaign decisions.

The work sits between research and product. You'll formulate research problems from product needs, test and extend methods from academia and industry, develop new approaches when existing methods fall short, and work with engineering and product to translate successful research into production systems.

Multimodal intelligence. Build systems that understand creators, brands, briefs, and content across video, audio, image, and text.

Ranking, recommendation, and prediction. Develop models that predict creator-brand fit and campaign outcomes and make better decisions from sparse, heterogeneous feedback.

Foundation models and agents. Apply LLMs and multimodal models to campaign planning, discovery, creative understanding, execution, and optimization. Use Agentio's proprietary data for prompting, retrieval, fine-tuning, post-training, and, where it makes sense, specialized model training.

Learning and decision-making. Turn campaign data into training signals, evals, and learning loops while tackling problems in optimization, exploration, measurement, and marketplace dynamics.

Part of the role is deciding which advances in AI and ML are useful for Agentio and where new methods are needed.

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  Own research problems from problem formulation through experimentation, validation, and product application.

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  Design rigorous experiments and evaluations, develop new methods where needed, and establish evidence that research advances improve product and marketplace outcomes.

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  Develop models, algorithms, training approaches, datasets, and evaluation methods when existing techniques are insufficient. Partner with engineering to turn successful research into reliable product capabilities.

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  Help define Agentio's research agenda, identify high-value research questions, and set a high bar for experimental rigor across applied ML work.

We're looking for a researcher with strong technical depth who wants their work to change a production product, not stop at a paper or prototype.

• PhD in machine learning, AI, computer science, statistics, or a related field, with a track record of original ML research demonstrated through peer-reviewed publications or comparable research contributions.

• Depth in one or more areas such as foundation models, multimodal learning, recommendation and ranking, representation learning, reinforcement learning and decision-making, causal inference, optimization, or adjacent fields.

• Experience applying research to real products or production systems, including turning ambiguous product problems into research questions and translating successful results into measurable product improvements.

• Strong implementation skills: you can prototype your own ideas, work directly with large datasets and modern ML stacks, and collaborate closely with engineers on productionization.

• Strong knowledge of current AI research and the judgment to distinguish technically interesting work from approaches that will matter in practice.

• The opportunity to build a first-of-its kind business as an early team-member and make a meaningful impact in the way brands share their stories and creators live off their work.

• Crash-course in what it takes to scale a start-up with first-hand exposure to the different foundational business drivers and needs.

• The chance to work with an exceptional team and help build our engineering culture

• A collaborative, transparent, and engaging work environment.