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We're looking for a Machine Learning Engineer who will build out and design machine learning infrastructure for a team of data & remote sensing scientists, working collaboratively with the Analytics and Software teams to deliver data-driven products and solutions.
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As a Machine Learning Engineer on the Banking & SFS team, you will support fellow Data Scientists and Modelers in building and deploying machine learning models that support our banking and lending business.
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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. Check out our Machine Learning / AI bloghere.
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Individuals in this role are expected to be recognized experts in identified research areas such as artificial intelligence, machine learning, AI applied to chemistry or material science, computational statistics, and applied mathematics, particularly including areas such as deep learning, graphical models, reinforcement learning, computer perception, natural language processing and data representation.
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Work cross-functionally with product, platform, security, and data engineering teams to unlock new machine learning applications. Passion about continuously learning new technologies, frameworks, and services.
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Learning and Development resources. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy.
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Train, tune and validate machine learning models using Tensorflow, python and GCP cloud infrastructure. Use techniques like LIME, SHAP, recent temporal pattern mining (RTP) to develop explainable machine learning models.
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Expertise in data science, machine learning, and artificial intelligence concepts, methods, and techniques, such as regression, classification, clustering, natural language processing, computer vision, or deep learning.
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Experience with the technologies listed above (e.g. Tensorflow, Kubernetes & Rust)Experience with robotics: arms, RGBD cameras, force sensors, etcExperience deploying machine learning models and/or systems in productionExperience working in startups/startup-like environment.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Matt has deep expertise in computer graphics and machine learning, and previously led the engineering team at Operator. Enable the Facet team to easily develop and deploy new machine learning capabilities at scale.
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Implement real-time cutting edge algorithms in signal processing, computer vision, and machine learning. Propose, prototype, and deliver to new methods and machine learning models to multiple production environments including Linux and mobile (iOS, Android.
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Programming Skills: Proficiency in programming languages like Python, R, or similar, along with experience in using machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
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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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Experience developing/training and maintaining models in multiple genres of Advanced Analytics: machine learning, deep learning, optimization/prescriptive modeling, NLP/text analytics, cognitive/generative AI.
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machine learning jobs Title: learning architect Company: Home Depot in San Francisco, CA
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