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Title- Lead/Sr Machine Learning Engineer - AWS (with LLM Focus) Containerization: Experience with Docker and container orchestration (e.g., Kubernetes, ECS) for LLM deployment. LLM Deployment Pipelines: Build and manage CI/CD pipelines specifically for LLM deployment, addressing unique challenges like model size, inference optimization, and versioning.
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As a Machine Learning Infrastructure Engineer , you will spearhead the architecture and development of the compute infrastructure essential for model training and deployment. About the Role of Machine Learning Infrastructure Engineer.
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Implement ML/OPS solutions using Azure ML, Databricks MLFlow, and LLMOps for streamlined Machine Learning operations. Manage Azure DevOps, CI/CD pipelines, GitHub, and Kubernetes (AKS) for efficient software development and deployment.
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Why would a Forward Deployment Engineer ever want to consider a career in (Re-)Insurance? Guy Carpenter (GC), the global leader in reinsurance brokerages, is seeking candidates for a Forward Deployed Analytics Engineer on its Data Strategy team, based in the New York City office.
$100,500 - $181,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The PTC Field Deployment Specialist ensures the safe and tactical execution and implementation of the Positive Train Control Systems (PTC) through active supervision of operating crews, S&C, Mechanical supervisors and employees.
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They should also be well-versed in Endpoint Detection and Response/Extended Detection and Response (EDR/XDR) integrations such as SentinelOne, Defender for Endpoint/Server, CrowdStrike, and Palo Alto Cortex XDR; along with experience with the deployment and configuration of Vulnerability Management tools (Qualys, Tenable.
$120,000 - $130,000 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Proven experience in Analog, ASIC & FPGA circuit & IP development, integration, and deployment, including all stages of development from circuit design, SI/PI, RTL place & route, timing closure, CDC/RDC.
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NLP, LLM, Gen AI Model Deployment: Work closely with the MLOps team for the deployment of machine learning models into production environments, ensuring reliability and scalability.
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Software Engineering & DevOps: Version Control: Familiarity with tools like Git. Continuous Integration/Continuous Deployment: Knowledge of pipelines and tools like Jenkins, Travis CI. Containerization: Familiarity with Docker, Kubernetes, etc., for scalable deployment of data science applications.
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The ME-i4.0 (Manufacturing Engineer Industry 4.0) will be a key member of the Eaton Aerospace Industry 4.0 deployment team responsible to drive the implementation of the smart factories across Eaton Aerospace Group.
$105,000.03 - $154,000.05 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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The Expert Data Scientist will be a champion of the latest Machine Learning and Artificial Intelligence technology stack. c#, informatic, java, machine learning, malware, photonics, processor.
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MUST: 5-7+ years working with SCCM and Intune, including image creation, customization, and deployment. Extensive experience 5-7+ years working with SCCM and Intune, including image creation, customization, and deployment.
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Has expert knowledge of standard data science and statistical techniquesHas a track record of successful deployment of machine learning models, frameworks, and their training, prediction time, and implications on production systemsHas strong knowledge of two of causal inference techniques, Gen AI (LLM) implementation, or contextual banditsExperience implementing scalable systems (Google Cloud preferred.
$165,000 - $190,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Responsible for designing and developing scalable UI solutions to facilitate the application of machine learning computational methods, and cloud resources to facilitate analysis such as drug data, natural language processing, molecular dynamics simulations, and image processing.
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Assist in Problem Solving: Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. Internal Collaboration: Collaborate closely with product teams, business stakeholders, Mlops, machine learning engineers, and software engineers to ensure smooth integration of machine learning models into production systems.
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deployment machine jobs Title: platform engineer Company: Baird
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