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As Staff Machine Learning Engineer, you’ll conduct applied research projects involving deep learning models from start to finish. You understand why machine learning will bring about the greatest turning point in human history.
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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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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, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Strong experience with Python/R, forecasting methodologies, machine learning and statistics, Xometry is an on-demand manufacturing marketplace that leverages machine learning (ML) techniques to predict the manufacturing cost of machined parts and produce automated buy it now prices on Xometry.com. Customers love our instant quoting engine, and that engine depends on Xometry’s ML team and technology.
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Our laboratory applies computational and machine learning methods to investigate the impact of seizures and abnormal brain activity on outcomes in pigs with cortical impact. The machine learning engineer will be responsible for data from the electronic data repository, including EEG, video, and peripheral blood biomarkers.
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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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Knowledge of Deep Learning and Machine Learning techniques, and experience in Machine Learning tools, techniques and programming (including LLM - Large Language Models) is a plus.
$160,000 - $170,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated 26 days ago - UpvoteDownvoteShare Job
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Potential Certifications: PMP, ITIL, PMI)Analytics: Database Technologies, Artificial Intelligence, Machine Learning, Data Science, Data Visualization. MIS: Management Sciences, Decision Sciences, Information Sciences, Product Management, Project Management, Program Management, Portfolio Management, Human Communications, Strategic PlanningAnalytics: Database Technologies, Artificial Intelligence, Machine Learning, Data Science, Data Visualization, etc.
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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.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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The Senior Principal Engineer- Site Reliability Engineering supporting Artificial Intelligence/Machine Learning/High Performance Compute Solutions, Service Delivery will be responsible for providing the primary management, administration, support, and ongoing maintenance of customer Platforms within a 24x7x365 datacenter 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.
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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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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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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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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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