Scale AI, Inc.
Machine Learning Research Engineer, Strategic Partnerships Lead
Scale AI, Inc., San Francisco, California, United States, 94199
Scale works with the industry’s leading foundation model labs to provide high quality data and accelerate progress in machine learning research. As a Machine Learning Research Engineer, you will design next generation data pipelines and supervision strategies in close collaboration with our customers to accelerate progress in Generative AI. The ideal candidate is highly technical and well-versed in recent research progress for LLMs, while also having great communication skills, customer obsession, and passion for evangelizing new research methods. Successful candidates will become true research partners to several top foundation model labs, contributing technically and strategically to the roadmaps for the next generation of large language models.You will:Collaborate closely with researchers from the top foundation model labs to design new strategies and data pipelines involving human supervisionPartner internally with Scale’s Data Engine team to bring your research and data pipeline ideas to lifeShape the roadmap for how post-training data is used to supervise the next generation of large language modelsConduct experiments for new research ideas in post-training, leveraging your unique vantage point as a technical partner to several labsAccelerate the meteoric growth of Scale’s Generative AI Data Engine business through deep technical partnership with our customersIdeally you’d have:At least 3 to 5 years of model training and/or deployment experience in a research or production environmentStrong skills in LLMs and deep learningExcellent written and verbal communication skillsNice to haves:Experience in dealing with large scale AI problems, ideally in the generative-AI fieldDemonstrated expertise in large vision-language models for diverse real-world applications, e.g. detection, question-answering, captioning, etc.Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, ICLR, etc.) and/or journalsStrong high-level programming skills (e.g., Python) and familiarity with at least one deep learning frameworkPrevious experience in a customer facing role
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