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Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 47 million monthly active customers.
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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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Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. The candidate will join a multi-disciplinary team of scientists and engineers and work on a full stack of developing cutting edge Computer Vision (CV) and Machine Learning (ML) methods based on data from a variety of sensors.
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Basic affinity or interest in machine learning/deep learning/artificial intelligence. Crafting internal tools that empower our our Machine Learning team to use to enhance search system quality and data.
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Relevant Keywords: Large Language Models, Machine Learning, Python, Deep Learning, Gemini, GPT, GPT-3, GPT-4, Synthetic Data, ML Fundamentals, Pytorch, TensorFlow, Data Engineering, Data Preprocessing.
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5+ years experience with applied Machine Learning or Deep Learning. 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.
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In Support Product we build highly available and scalable, Machine Learning driven products that integrate with the broader Cash App ecosystem to help customers solve their problems. The team currently consists of server engineers, designers, and product management, machine learning modelers and applied machine learning engineers located in Australia and the United States.
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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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Statistical/data science methods most commonly used in retail analyses including: forecasting, AB testing, hypothesis testing, machine learning and prediction algorithms; Access, query, aggregate, manipulate, consolidate, and summarize omni-channel customer and visitor data from multiple large-scale data sources using data science tools (SQL,R, Python, SAS, Microsoft Power BI, Azure, Adobe, Databricks.
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Senior Machine Learning Engineer AtanAI Boston, MA, Brooklyn, NY, San Francisco, CA, Washington, D.C., Remote, London, England 11-10-2023 HealthTech Azure Elasticsearch Docker AWS Python Machine Learning.
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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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Insitro is pioneering a new approach to drug discovery and development, enabled by the use of advanced machine learning (ML) to interrogate large amounts of cellular, molecular and clinical data.
$245,000 - $275,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Implement Common Core State Standards-aligned and Science of Reading-aligned curriculum and lessons that build and integrate rigorous and student-centered learning experiences in English in partnership with Mandarin Chinese co-teacher leading other subjects (i.e. Chinese language arts, mathematics, social science, science.
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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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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency.
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machine learning jobs Company: Seagate Technology in San Francisco, CA
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