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Our team develops, implements, and maintains recommendation and personalization algorithms for Disney Streaming’s suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
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Consulting and/or CxO roles with 15+ years of progressive technology exposure (AI - including Machine Learning, Natural Language Processing, Deep Learning, Robotics, Product Development, BI, Digital Transformation, Block Chain, Big Data, High Performance Compute, Cloud, etc.
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Our transformative solutions are powered by artificial intelligence, machine learning, facial recognition, cloud solutions and Big Data analytics. Our transformative solutions are powered by artificial intelligence, machine learning, learn from new insights, and seize new opportunities.
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We aim to leverage cutting edge technologies in big data, machine learning, and optimization techniques, and operate high volume, low latency, and high availability services.
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Experience with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc. Familiarity with advanced machine learning architectures GANs, GRU, LSTMs, RNNs, CNNs, style transfer.
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We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
$176,700 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Expertise in machine learning, statistical modeling, data visualization, and familiarity with big data technologies and cloud platforms including AWS, Azure, or Google Cloud.
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We are seeking a Principal Architect to join our growing team of talented AI Architects, Machine Learning Engineers and Data Scientists. Understanding of machine learning algorithms such as Linear and Logistic regressions, Decision tree, Naive Bayes, KNN, K-means, Random Forest.
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Familiarity with Data Analysis and Machine Learning Tools and Libraries like Jupyter Notebooks, Pandas, SciPy, Scikit-learn, Gensim, tensorflow, pytorch, etc. Experience in effective data engineering practices and big data platforms such as BigQuery, Data Store, etc.
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Processing billions of data points a day, Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety and achieve strong compliance to regulatory changes.
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Building these controls requires knowledge of big data techniques, ability to architect systems that can efficiently scale to hundreds of billions of data points per day, machine learning over unstructured and structured data, graph analytics, and experience with building UI for data rich applications.
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Experience with Big data technologies such as AWS EMR, Spark, Machine Learning (AWS SageMaker) and one or more cloud environments (AWS, Google and Azure) Softrams is a Maryland and Virginia-based small business information technology, consulting, and solutions provider specializing in emerging technologies for UX/UI, mobile apps, DevOps, big data analytics, data science, and cyber security.
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The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
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Experience in machine learning, big data analytics, data science, and cloud computing is a plus. Qualified candidates need to be passionate about the Machine Learning and Artificial Intelligence space, will excel in problem-solving and combine an advanced business or technical degree with consulting or product management experience and have a record of successful delivery of complex, multi-faceted projects.
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Data Science, Machine Learning, or Deep Learning experience is a plus. Experience leveraging big data technologies (Hadoop, Netezza, Vertica, AWS, etc) and modern data visualization tools (Tableau, ThoughtSpot, Looker) to blend data from multiple sources to help answer multi-dimensional business questions.
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