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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 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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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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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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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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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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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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We are seeking a Senior Machine Learning Engineer to join DS&E. Candidates should possess robust knowledge and hands-on experience in end-to-end ML modeling, including design, development, deployment, monitoring, and maintenance, plus proficiency with cloud computing infrastructure, AWS in particular.
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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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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. AWS, AlienVault, Azure, Bash, Confluence, EKS, GSuit, Github, Golang, HTML, Hashcat, JIRA, JWT, Java, Javascript, Jenkins, Kubernetes, Metasploit, New Relic, Nmap, NodeJS, OWASP, Okta, PCI-DSS, PagerDuty, Python, Rails, Ruby, SAML, SQL, SQLMap, SignalScience, SignalSciences, Slack, Snyk, Sumologic, tenable.io, Twistlock, TypeScript, Wireshark, tcpdump.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.
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Develop and implement train machine learning models using Google Vertex AI and Typescript, Express. Design, build, deploy machine learning models and microservices on the Google Cloud Platform.
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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.
Full-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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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.
Full-timeExpandApply NowActive JobUpdated 5 days ago
machine learning jobs Title: electrical engineer Company: Optello
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