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Research Engineer, World Models Jobs

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256000.00 - 320000.00 USD / Year
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Quantitative Researcher
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Principal Applied Scientist - Small Language Models
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Microsoft Corporation
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Senior Machine Learning Engineer
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Microsoft Corporation
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Developer Advocate AI/ML
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Product Lead for Participants
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Safety Engineer Expert – Machine Learning - ISO 26262
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Explore cutting-edge Research Engineer, World Models jobs and step into a role at the forefront of artificial intelligence and autonomous systems. A Research Engineer specializing in World Models is a hybrid professional who bridges the gap between theoretical AI research and practical, scalable engineering. Their core mission is to develop and refine large-scale generative models that learn a predictive understanding of how environments evolve. These "world models" are foundational AI systems designed to simulate and anticipate future states based on past sensory inputs and actions, a capability critical for advancing robotics, simulation, and general AI agents. Professionals in these roles typically engage in full-stack AI development. Common responsibilities span the entire model lifecycle. This includes designing and implementing high-throughput data pipelines to process vast, multi-modal datasets encompassing video, sensor data, text, and action sequences. They architect and train complex neural network models, often based on transformer or other advanced architectures, tailored to handle this diverse data. A significant part of the role involves not just pure research but also product-oriented engineering, translating model improvements into tangible enhancements in system autonomy and performance. They rigorously analyze scaling laws and predictive metrics to guide model development and pre-training strategies. To succeed in Research Engineer, World Models jobs, individuals require a robust and interdisciplinary skill set. Technical proficiency in Python and deep learning frameworks like PyTorch is fundamental. Strong experience with distributed training, data loader optimization, and software engineering best practices is essential for handling web-scale data. A deep understanding of generative model architectures, particularly for multi-modal prediction, is a key requirement. Familiarity with simulation environments and a solid grasp of machine learning fundamentals, including loss metrics and scaling behavior, are standard expectations. Beyond technical skills, these roles demand strong problem-solving abilities, as engineers must creatively tackle challenges in making abstract world models function reliably in complex, unstructured scenarios. For those passionate about building the predictive brains of future AI systems, Research Engineer, World Models jobs offer a dynamic and impactful career path. This profession sits at the exciting intersection of research innovation and hands-on engineering, pushing the boundaries of what machines can understand and predict about the world around them.

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