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Job Description: As a Senior Machine Learning Engineer, you will lead the development and implementation of sophisticated data engineering solutions to support the deployment and optimization of AI models.
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Provide technical design and architectural leadership to multiple teams and projects to help ensure applications are integrated and adhere to stated architectural and design principles and standards while having the opportunity to remain in a hands-on engineering role.
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Proven, hands-on experience in data modernization projects, including data migration, data warehousing, and data governance. Hands-on experience with GCP data services, including BigQuery, Dataflow, Dataproc, Dataprep, Composer, Data Fusion, Data Studio, Cloud SQL, Cloud Functions and Cloud Storage.
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Leading team in the definition of best practices & repeatable methodologies in Cloud Data Engineering, including Data Storage, ETL, Data Integration & Migration, Data Warehousing and Data Governance.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Have a background in software engineering, DevOps, artificial intelligence and machine learning. The role will concentrate on machine learning research, production, deployment involving data, databases, displays, stack management, Kubernetes, large-scale infrastructure, and experiment management.
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What you’ll bring to Circle: 5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Bachelor’s degree in Data Science, Statistics, Computer Science, applied mathematics, machine learning, or a related data centric-technical field. Hands-on experience in Azure Databricks.
$108,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 15 days ago - UpvoteDownvoteShare Job
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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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 looking for a hands-on machine learning engineer who is passionate about crafting, developing, and deploying cutting edge AI/ML solutions which will impact millions of customers.
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As our first Data Science hire focusing on Machine Learning at Circle, you’ll start by focusing on two critical problems: helping identify transactions and actors who might be acting illicitly and helping us better balance our reserves across a series of accounts to reduce systemic risk inside the company.
$147,500 - $195,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Proficiency in data engineering concepts, tools, and technologies, with hands-on experience with Databricks or similar platforms. Manage and support the Data Engineering team responsible for leveraging Databricks for data processing, analytics, and machine learning.
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FM Global is seeking a Machine Learning Operations Data Engineer II to join our AI/ML team to support Machine Learning Engineering, working very closely with Data Science, Data Engineering, Subject Matter Experts and Solution Architecture teams.
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Infrastructure Operations: Minimum 3 to 7+ years of hands-on experience in some combination of the following technologies: Azure (VMs, Web Apps, Managed Databases), GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, Linux/Windows VM administration, Shell scripting (primary Bash but PowerShell as well.
$88,400 a yearFull-timeExpandApply NowActive JobUpdated Today
hands on machine learning data engineering in person jobs in United-states, District Of Columbia
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