Applied Research Scientist

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Description

San Francisco, CA · Full-time The Role We're looking for an Applied Research Scientist to own applied research on organic AI alignment end-to-end. You'll choose the question, design the environment configs and evaluations, implement experiments, analyze results, and turn what works into reusable systems. In this role, research and execution go hand in hand: you generate clarity from ambiguity and produce conclusions that survive contact with reality. This role is focused on training new model families. You should be comfortable reasoning from first principles about architectures, losses, optimization, curricula, scaling behavior, and failure modes. You'll help train a new generation of RL approaches: systems that can stream, adapt, grow, and keep learning over time. You're fluent in modern AI tools and use them across coding, literature review, experiment design, analysis, and writing. You use that leverage to take on harder problems, not just to iterate faster. What You'll Do Choose and run high-leverage experiments. Translate model-training and alignment questions into concrete architectures, tasks, curricula, evaluations, and experiments; run them, interpret them, and iterate.Train new deep learning architectures from scratch. Work with novel model substrates, loss functions, data mixtures, recurrent computation, graph structure, and scaling recipes to discover what actually trains.Run rigorous experiments. Use ablations, baselines, controls, and statistical judgment. Unde

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