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About The RoleAs a Principal Engineer on the AI Ops team, you will be responsible for building the next-generation routing engine for the Internet using Data Science, Machine Learning (ML), and Artificial Intelligence (AI.
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Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform, and services like AWS SageMaker, Azure Machine Learning, or Google AI Platform. Position Overview: As a Senior Machine Learning Infrastructure Engineer, you'll lead the design, development, and optimization of our machine learning infrastructure.
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The mission of the Waymo Applied Research team is to develop machine learning solutions addressing open problems in autonomous driving, towards the goal of the safely operating Waymo vehicles in dozens of cities and under all driving conditions.
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Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases. Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
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Experience building tools that are core to a machine learning engineer’s daily work. Build automation that surfaces insights on how machine learning engineers can improve workflow efficiency.
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Machine learning techniques, including, but not limited to, deep learning. Hands-on experience with machine learning techniques is mandatory, preferably including deep neural methods.
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Including two-thirds of high school students and half of all college students in the US. Combining cognitive science and machine learning, Quizlet guides students through adaptive study activities to confidently reach their learning goals.
$150,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Below you'll find an outline of the interview plan for our Senior Machine Learning Engineer position. You are an expert with Docker, Kubernetes, and scaling machine learning solutions.
$151,000 - $177,000 a yearExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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The Data Science and Machine Learning team work on a range of classification and optimization problems, e.g. search ranking, text/sentiment classification, and/or collaborative filtering/recommendation, to deliver the world's quality information to the people who need it.
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Our growing Customer Success team is looking for a passionate and enterprising Machine Learning Solutions Engineer. Significant knowledge of the artificial intelligence ecosystem; a deep understanding of how data scientists and machine learning engineers develop and deploy AI models.
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Publications or presentation in recognized Machine Learning, Deep Learning and Data Mining journals/conferences · Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call.
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We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, and computational statistics.
$117,000 - $137,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Hands-on experience with machine learning and NLP tools and libraries from Numpy to PyTorch. As a Staff Machine Learning Research Scientist you will work on some of the deepest problems in machine learning.
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ArsenalBio, a privately held, clinical-stage programmable cell therapy company engineering advanced CAR T therapies for solid tumors, is seeking a talented Scientist I, Computational Biology & Machine Learning to work hybrid based in our South San Francisco office.
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Design and implement scalable machine learning and distributed systems that enable training and scaling of LLMs across HPC clusters. We are well-capitalized and supported by March Capital and Thrive Capital, with participation from AMD, Franklin Venture Partners, Google, KB Investment, NVIDIA.
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machine learning jobs in San Francisco, CA
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