Agentio
Research Engineer, Applied AI
About this role
Agentio seeks a Research Engineer to advance AI-native creator advertising through applied ML research. You'll develop multimodal models for ranking, recommendation, and decision-making, working with foundation models and proprietary data to ship production systems that improve campaign predictions and creator-brand matching.
What you'll do
- Own research problems end-to-end from problem definition through production deployment
- Evaluate and adapt existing AI/ML methods against proprietary data with rigorous experiments
- Develop novel models, algorithms, and training approaches when current techniques are insufficient
- Build multimodal systems understanding creators, brands, and content across video, audio, image, and text
- Collaborate with engineering and product teams to ship research into production
- Help establish Agentio's research agenda and ML technical standards
What they're looking for
- Applied machine learning research with production systems experience
- Multimodal learning and foundation models
- Recommendation systems and ranking algorithms
- Reinforcement learning and decision-making
- Strong software engineering and ML systems design
- Experimental rigor and evaluation methodology
- Python and ML frameworks
- Current AI research knowledge and practical judgment
Benefits
- Flexible PTO
- Comprehensive health coverage through Aetna
- Dental and vision plans
- 401(k) retirement plan
- $100 monthly lifestyle credit
- Daily office lunches and snacks
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Agentio
Agentio builds AI-powered solutions for recruiting and creator-led advertising marketplaces, with technology that automates and optimizes talent decisions and campaign management at scale. The company is hiring software engineers and systems specialists to develop intelligent systems, full-stack features, and marketplace infrastructure.
View all jobs at AgentioLikely interview questions
- Describe a production ML system you've built—how did you approach the research-to-production transition?
- Walk us through how you'd approach building a multimodal model for creator-brand compatibility given sparse feedback data.