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Familiar with a range of machine learning models; for example: Random Forest, GBM, XGboost, GLM/glmnet, Deep learning convolutional models, recurrent models, and dimensionality reduction methods, including PCA, SVD , Isomap.
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PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centered in Machine Learning and Deep Learning) with 3+ years relevant experience is preferred but not a must; OR.
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Coursework or hands-on experience in building advanced machine learning techniques, including GBM’s, deep learning models, embeddings, Graph Neural Networks (GNNs), transformers, etc.
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To accelerate our customers transformation leveraging cloud, we combine world-class learning and talent development expertise; deep experience in cloud change management; and cloud-ready operating models with a commitment to responsible business by design — with security, data privacy, responsible use of artificial intelligence, sustainability and ethics and compliance built into the fundamental changes Accenture helps companies achieve.
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Gain real-world sales experience, take a deep dive into the vast staffing. will also shadow Account Managers gaining an insight into sales by learning. You’ll begin in the Recruiter role, learning to source, interview, and.
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The ideal candidate will have a strong background in digital advertising, experience ideating and managing programmatic campaigns, and a deep understanding of programmatic technologies. IXL Learning, a leading EdTech company with products used by 15 million students worldwide, is looking for a Programmatic Manager.
$100,000 - $120,000ExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Our founding team has deep expertise in financial services, product engineering, data science, and machine learning, as well as degrees from MIT, Harvard, Columbia, Georgetown, and Yale. We try to take a scientific, data-driven approach whenever possible.
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Programs on 5G, quantum computing, artificial intelligence, deep learning, quantum computing and from artificial intelligence and deep learning to cyber. programs on 5G, quantum computing, artificial intelligence, deep learning.
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Sustained (e.g., at least 10 years), hands-on experience with: data modeling and data engineering, feature engineering, model lifecycle management, and cloud infrastructure; supervised and unsupervised deep learning algorithms.
Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing. 5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), artificial intelligence, deep learning, or natural language processing.
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Passion for Artificial Intelligence and Machine Learning: Demonstrated a deep interest and enthusiasm for the field, stayed up-to-date with the latest advancements and trends. Lead Development: As the lead engineer, you will spearhead the development of the next generation of machine learning software.
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You will work alongside other ops engineers, data scientists, software engineers, and machine learning research engineers to help deliver some of the most crucial data to deep rooted algorithm development that is used to drive functionality to millions of devices and users all over the world.
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Have expertise in Machine Learning best practices (e.g. model evaluation and hyperparameter tuning, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection.
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We have a new vision: forging a retail winner that is admired for national strength with deep local roots, that offers an easy, fun, friendly, and inspiring experience, no matter how a customer chooses to shop with us.
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Partner with our Application Health team to explore real-time, predictive analytics and machine learning on operational and business data captured on the SDP. Established track record with GCP technologies (administration, configuration, and troubleshooting), with hands-on production experience and a deep understanding of the GCP architecture and internals of how it works, along with interplay of architectural components.
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