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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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Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. , and our core team includes faculty entrepreneurs (Stanford) and industry veterans (Uber, Apple, Amazon Lab126, Rohde & Schwarz), who have successfully shepherded signal processing and machine learning innovations to large-scale software for location improvement and safety at Uber.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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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. Experience with Azure cloud services, particularly Azure Machine Learning and Azure Databricks.
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We were founded in January 2016 by former executives and engineering leaders from Google and Uber. We are funded by some of the world's best investors and entrepreneurs including Founder's Fund, Khosla Ventures, First Round Capital, Eric Schmidt (Google/Alphabet Chairman), Marc Benioff (Salesforce Founder), Joe Lonsdale (Palantir Founder), Joshua Kushner (Oscar co-Founder) and Garrett Camp (Uber co-Founder).
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We are seeking individuals with a profile of skills in psychometrics, statistical computing & programming, simulation-based research, natural language processing, and machine learning. Increasingly, we find ourselves conducting data analyses of rising complexity involving traditional statistical methods alongside techniques related to machine learning.
ExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Provide technical expertise and support to POD teams in the development and implementation of machine learning and AI solutions, leveraging Azure, Databricks, and MLflow. 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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Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree. Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science.
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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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Title URBN Machine Learning Engineer Reports to Sr. Manager, ML Engineering Overview The URBN Data Science organization is responsible for building, deploying, and maintaining Machine Learning systems to support the URBN brands.
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Hands on experience working in an infrastructure managed services environment, supporting complex engineered solution in production with Artificial Intelligence/Machine Learning/High Performance Compute Systems and Platforms, Converged/ Hyper-Converged infrastructure along with fluency in AI/ML pipelines, Nvidia GPU optimization, InfiniBand networking, Machine Learning operating systems such as cnvrg.io, Compute Orchestration Platform such as runai etc.
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The postdoc will work help NASA and end users deploy machine learning models of high accuracy, and work with existing research assistants and post docs to improve deep learning models of inundation.
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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.
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As a Senior Machine Learning Engineer, You Will Be Building a Platform That Accelerates Drug Discovery With Machine Learning For a Wide Variety Of Use Cases With Respect To Data Modality, Model Architecture, And Model Size. By Leveraging Your Experience In Machine Learning, Software Engineering, Infrastructure, And Data, You Will.
$170,000 - $192,000 a yearFull-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Established expertise and genuine passion for natural language processing (NLP), machine learning, deep learning, and large language models. Experience crafting machine learning models in cloud environments like AWS or GCP, with specific knowledge of Sagemaker being a plus.
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machine learning jobs Title: learning architect Company: Meta
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