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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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As a machine learning engineer, you’ll have the opportunity to immediately drive a huge, direct impact for Propel! Lead Propel in building machine learning infrastructure that all teams can take advantage of.
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As a Staff Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. We are looking for Staff Machine Learning Engineers of all skill levels or experienced engineers from other disciplines who may be looking to make the move to a big data environment.
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Databricks Certifications (ie: Data Engineer Associate; Data Engineer Professional, Machine Learning Associate, Machine Learning Professional) Collaborating amongst team members across several geographies, our Cloud practitioners engineer cloud-based analytics solutions on AWS, Azure, Databricks, GCP, Snowflake, Oracle, Informatica Cloud and a combination of native cloud technologies, including computing at edge and curating data-in-motion.
$119,025 - $198,375 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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You’ll be spearheading Propel’s work to leverage machine learning algorithms across our teams. Continually source new machine learning and recommender system innovations from industry, academia, etc.
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Experience with Cloud using Amazon Web Services (AWS), Microsoft Azure, and/or Google Cloud Platform (GCP) Experience with Databricks Unity Catalog. 2+ years experience implementing data solutions on the Databricks Data Intelligence platform, to include Delta Lakes.
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Experience with Databricks. We serve as a trusted advisor and managed service provider bringing a mix of capability and capacity across data modernization, data ops, AI, and ML. Through our unrivaled breadth and depth of services across every major industry and domain, we help our clients run smarter, faster, and more efficiently.
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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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As a Google Vertex Full Stack Software Engineer, you will be responsible for developing and implementing machine learning models using Google Vertex AI and developing consumable API microservices using Typescript, Node.js, Express.
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The machine learning engineer will be responsible for data from the electronic data repository, including EEG, video, and peripheral blood biomarkers. The machine learning engineer will work and mentor a team of researchers in searching for patterns hidden in large data sets for research in neurology.
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We are seeking a skilled Machine Learning Engineer with expertise in Azure, Databricks, and MLflow, as well as strong full-stack capabilities, including experience with React. As a Machine Learning Engineer supporting POD teams, you will play a pivotal role in providing technical expertise and guidance to ensure the successful development and delivery of machine learning and AI solutions.
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Experience with Azure cloud services, particularly Azure Machine Learning and Azure Databricks. Provide technical expertise and support to POD teams in the development and implementation of machine learning and AI solutions, leveraging Azure, Databricks, and MLflow.
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5+ years of experience in machine learning engineering, data science, or a related field. Your responsibilities will include collaborating closely with product teams, contributing your expertise in machine learning technologies, and leveraging your full-stack capabilities to support the implementation of frontend components using React.
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Leveraging this therapeutic bond, and the expertise of our Stanford-trained clinicians and scientists, Woebot is constantly learning from the experience of more than one million people and hundreds of millions of messages exchanged to deliver high quality CBT-based therapeutic tools that are psychologically related and responsive to a person’s dynamic state of health.
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Assist in the deployment of machine learning models into production environments, implementing monitoring and logging mechanisms for performance tracking. Collaborate with frontend developers to support the implementation of responsive and user-friendly web interfaces using React, integrating machine learning capabilities seamlessly into frontend applications.
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