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Machine Learning is an integral part of how we design products, operate, and pursue Cash App’s mission to serve the unbanked as well as disrupt traditional financial institutions. Identity: Using machine learning methods and systems, this team reduces the prevalence of inauthentic identities in Cash’s ecosystem, provides a first line of defense against bad actors attempting to circumvent our IDV controls while simultaneously building our confidence in existing and new customers' identities.
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The ideal candidate will have a solid background in machine learning and statistical modeling, The Lead AI/ML Engineer will play a key role in developing and implementing data-driven strategies to improve lead generation and lead scoring, customer segmentation, and marketing automation activities.
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Typical role includes working on a wide range of activities such as working with complex structured and unstructured datasets, developing/recommending novel machine learning tools, data visualizations, automation of analytics workflows, disease progression models, mechanistic and empirical PK/PD models, clinical trial simulations, literature meta-analysis using quantitative approaches and statistical modeling of historical and preclinical data.
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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.
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As an applied scientist on Twitch's Community team, you will use machine learning to develop data products tackling problems such as harassment, spam, and illegal content. - Build machine learning products to protect Twitch and its users from abusive behavior such as harassment, spam, and violent or illegal content.
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Familiarity with Artificial Intelligence/ Machine Learning, Robotics Process Automation and Blockchain and their impact on the regulatory environment. Transaction tax engine experience (e.g., Vertex, Thomson Reuters, Avalara.
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Our next-generation platform, which combines threat intelligence with machine learning, enables financial institutions and governments to detect cryptocurrency fraud and financial crime at an unprecedented scale.
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As a Quantitative Analyst at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.
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Proven experience in machine learning and classification. Expertise with parallel training, active learning, model deployment (e.g., TensorRT conversion) Our technology stack includes Generative AI models (GPT) and Reinforcement Learning (RL.
$183,600 - $270,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Nice to have - You have some basic affinity or interest in machine learning / deep learning / artificial intelligence. You will work closely with experienced machine learning scientists to develop and ship cutting-edge tooling, and user-facing products.
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Ideal candidate would have industry experience in the field of Artificial Intelligence, Machine Learning, and/or Cloud Computing. We look forward to speaking with you, and learning more about what you are seeking in your next opportunity.
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Familiarity with AI (Artificial Intelligence) subsets such as Machine Learning, Large Language Models (LLM) and Natural Language Processing (NLP). Our team creates world-class immersive digital experiences for the Company's premier vacation brands including Disney's Parks & Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club.
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The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning and deep reinforcement learning, or natural language processing into a production environment to improve scale.ai’s products and customer experience.
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Experience with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure, and familiarity with cloud services for machine learning (e.g., SageMaker, AI Platform, Azure ML.
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Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or appliedmathematics as necessary to carry out role effectively. Partners with machine learning engineers, BI, and solutions architects to develop technical architectures forstrategic enterprise projects and initiatives.
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machine learning jobs Title: district manager in San Francisco, West-greenwich, Rhode Island
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