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Knowledge of data science, machine learning, and artificial intelligence is required. Knowledge of data science, artificial intelligence, and/or machine learning is required.
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We achieve this vision by providing unified, configuration-driven, and fully orchestrated machine learning APIs, customer-facing declarative interfaces and various microservices for the entire machine learning lifecycle including Data, Training, Predictions/scoring, Orchestration, Model Management, Model Storage, Experimentation etc.
$265,200 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (, AWS, Google Data Analytics, Microsoft Azure) Information for applicants with a need for accommodation: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
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The faculty member will establish a research program focused on leveraging machine learning methods to integrate multiple modalities of data (e.g., EHR, imaging, genomics) including environmental exposure data into computational models for prevention, diagnosis, and treatment of breast cancer, and for mechanistic understanding of breast cancer etiology.
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Responsibilities: Designing and building large-scale machine learning systems including data transformation pipelines, feature stores, distributed training, architecture optimization, model management & serving, etc.
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Develop state of the art LLM based automated rating systems leveraging the Scale ecosystem for customized training data. AWS or GCP) and developing machine learning models in a cloud environment.
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The specific areas of expertise should include big data analytics, visualizations, biomarker data repository development, clinical decision support, bioinformatics, clinical research informatics, machine learning, clinical trials, and related areas.
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Experience with deep learning libraries (e.g. PyTorch, Jax, Tensorflow) and platforms, multi-GPU training, and statistical analyses of observational and experimental data. Whether it’s holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.
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This is an opportunity for a Machine Learning Engineering Manager to come in and drive Data Science and ML initiatives for the enterprise. As Manager of Machine Learning engineering team, you will work on a broad set of domains that power a data-driven transformation of our standard business procedures across channels.
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Mosaic AI is hiring experienced machine learning platform engineers to build out our generative AI platform for the ML model development lifecycle including pre-training of large language models (LLMs), fine-tuning, evaluation, and serving.
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Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D(with good publications in A. Experience building a LLM or other large models from scratch including writing model code, gathering training data, optimizing training and inference.
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Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.
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As a Senior Software Engineer in the Central AI team, you will build and maintain the core infrastructure to allow machine learning engineers and data scientists to develop, train, evaluate, deploy, and operate Machine Learning models and pipelines.
$265,800 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Machine Learning Engineer, Post-Training, you will work across teams and our technical stack to improve our model performance and training methods, including data, compute and algorithms.
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Founded in late 2020 by a small group of machine learning researchers, Mosaic AI enables companies to create state-of-the-art AI models from scratch on their own data. Experience with compiler technologies relevant to machine learning.
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