AI Researcher — AI Architecture Research at Featherless AI | Torre
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AI Researcher — AI Architecture Research

You'll design novel AI architectures, publish impactful research, and deploy real-world systems.
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Emma of Torre.ai
1 day ago

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About the RoleWe’re looking for an AI Researcher focused on AI architecture research to help design, analyze, and advance next-generation model architectures. You’ll work at the intersection of theory and production—publishing novel research while collaborating closely with engineers to turn ideas into real systems.This role is ideal for someone who has published research papers and wants to see their work directly shape deployed models, not just benchmarks.What You’ll Work OnResearch and design novel AI architectures (e.g. alternatives to standard Transformer designs, long-context models, efficient sequence modeling, hybrid architectures)Explore architectural improvements for scalability, efficiency, and stabilityPrototype and evaluate new architectures through ablations, benchmarks, and empirical studiesAuthor and co-author research papers for top ML conferences and journalsCollaborate with engineering teams to translate research into training and inference systemsStay current with state-of-the-art research and identify promising directions earlyWhat We’re Looking ForStrong background in machine learning research, with a focus on model architecturePublication record in ML/AI venues (e.g. NeurIPS, ICML, ICLR, COLM, ACL, EMNLP, arXiv)Deep understanding of:Neural network architecturesSequence models and attention mechanismsTraining dynamics and optimizationHands-on experience with PyTorch or JAXAbility to reason rigorously, design clean experiments, and communicate results clearlyComfortable working in a fast-moving startup environmentNice to HaveExperience with non-Transformer architectures (e.g. RNN-based, state-space, hybrid models)Work on long-context or memory-efficient modelsOpen-source research contributionsExperience bridging research and production systemsBackground in efficient training or inference-aware architecture designWhy Join UsHigh ownership over research direction and roadmapClear path to publishing impactful workTight feedback loop between research and real-world deploymentSmall, highly technical team with strong research cultureCompetitive compensation and meaningful equity
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