Research Engineer, Applied AI
Agentio · New York, NY
About this role
## About Agentio 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. We’re looking for a **Research Engineer, Applied AI** to advance this work through applied AI and ML research—developing models that improve the platform’s predictions and automate more of the decisions behind creator advertising. The work spans research and production. You’ll evaluate methods from academia and industry, adapt and train models on Agentio’s proprietary data, develop new approaches when existing methods fall short, and work with engineering and product to ship them. --- ## What You’ll Work On ### 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**, making 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 optimization, exploration, measurement, and marketplace dynamics. Part of the role is deciding which advances in AI/ML are useful for Agentio and where new methods are needed. --- ## What You’ll Do - **Own research problems** from problem definition and experimentation through production. - Evaluate relevant **AI/ML methods** against Agentio’s data; build rigorous experiments and evaluations; measure performance in production. - Develop **models, algorithms, training approaches, or datasets** when existing techniques aren’t sufficient; partner with engineering and product to ship successful approaches. - Help set Agentio’s **research agenda** and technical standards for applied ML. --- ## Who We’re Looking For - Strong research judgment **and** a desire to build production systems. - Demonstrated experience conducting applied ML research, with original work shown through production ML systems, publications, open-source research, or comparable contributions. - A **PhD or advanced degree** in ML/AI/CS/statistics (or related) is useful but not required. - 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 - adjacent fields - Ability to turn ambiguous product problems into tractable research questions, run rigorous experiments, and translate results into production. - Strong engineering skills and experience taking ML work beyond prototypes. - Strong knowledge of current AI research and the judgment to determine what’s useful in practice. --- ## What You’ll Get
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