Real-World AI Research Intern (PhD)
About The Position
Palona builds real-world AI systems that operate continuously in production. Our work focuses on AI agents that perceive, reason, remember, and act in physical environments, starting with restaurants as a constrained but high-signal domain. We are interested in research that survives contact with reality: partial observability, delayed effects, noisy signals, non-stationarity, and long-horizon outcomes. This internship is for PhD students who want to work on applied research problems grounded in deployed systems. You will work on questions that arise from live AI agents operating in the real world, where clean assumptions break and system behavior must be understood over time, not just measured offline. Projects are scoped based on your expertise and may include: Designing world state representations that persist across time, entities, and events Modeling cause and effect in real operational workflows Building reasoning systems that operate with partial observability and delayed outcomes Developing evaluation methods for agents running in production Translating research ideas into systems that are deployed and iterated on You will collaborate closely with senior researchers and engineers and see how your work affects system behavior in the real world.
Requirements
- Current PhD student in CS, AI, ML, Robotics, or a closely related field
- Strong research record (publications or equivalent contributions)
- Hands-on experience implementing research ideas in code
- Solid foundations in machine learning and statistical reasoning
Nice To Haves
- Experience with deployed or real-world ML systems
- Prior industry or applied research experience
- Strong Python and ML systems skills
Benefits
- Exposure to research problems shaped by real deployment constraints
- End-to-end ownership from research idea to production impact
- Close mentorship from experienced AI practitioners
- Opportunity for continued research collaboration beyond the internship
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
11-50 employees
