Staff Generative AI Research Engineer, Reasoning & Memory - SIML

We are seeking a candidate with a track record in algorithm development for agentic reasoning & memory. Key attributes expected in the role are fluency in algorithm development (prompt optimization and post training), strong expertise with relevant techniques (reinforcement learning, multimodal reasoning), and experience with automatic evaluation approaches for agentic workflow. The role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling & data infrastructure is desired. PhD, or MSc in Computer Science/Electrical Engineering, or a related field (mathematics, physics or computer engineering); with a focus on machine learning, or comparable professional experience Strong ML and Generative Modeling fundamentals Strong expertise in one of the following: Reinforcement Learning, Multimodal Training, Pre-training / Post-training foundation models Proficiency in using ML toolkits, e.g., PyTorch Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm Experience with building & deploying Multimodal-LLMs Familiarity with distributed training and large-scale data infrastructure

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