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How you’ll make an impact: As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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Minimum of 5 years of experience in machine learning and AI, with a focus on large language models and generative AI.Versioning control tools, Git, Gitlab, CICD tools, Dockers and KubernetesKnowledge of data science, machine learning & deep learning models and expertise in statisticsExperience with machine learning frameworks such as TensorFlow, Keras, or PyTorch and other open sources ML frameworks.
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And will contribute to the assessment and implementation of novel analytic approaches involving digital image analysis, machine learning and other emerging technologies critical to the continued scientific leadership of BMS. The successful candidate will also provide pathology subject matter expertise to clinical trial teams spanning early to late-stage development, and will have opportunities to engage with key academic partners on BMS supported research studies.
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Experience managing and analyzing large data sets using data science tools such as artificial intelligence and machine learning. Through a highly effective Investment Process, they provide solutions across all product platforms and asset classes - equity, fixed income and alternative investments including structured products and specialty assets - through a comprehensive due diligence and oversight process for client portfolios.
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The team's work is essential in supporting feature developments that use artificial intelligence and machine learning including Bloomberg Law's Docket Key, Points of Law, Brief Analyzer and Draft Analyzer, Bloomberg Tax's search capabilities and Bloomberg Government's State Bill Comparison.
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Duties: Improve value to the business and patients through deepened market understanding, streamlined business engagement and practically applied, data driven analytics by drawing on experience with natural language processing using R or Python; regression and classification using Machine Learning; managing large analytical projects with matrix teams in global setting; development of analytical platform using business intelligence tools; and cloud-based technology.
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Applicants should have training and a significant track record in one or more of the following areas: -AI, deep learning methods-atmospheric, climate, and/or weather modeling-computer science, statistics, and/or machine learning with applications relevant to genomics-population genetics / genomics.
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Develops and executes strategies to identify and fulfil complex information needs company-wide using advanced techniques, methodologies, and technologies in text-mining, natural language processing, data mining, machine learning, and data visualization.
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Understand the impact of key technology trends and workforce changes impacting our clients through engagement with innovative and emergent technologies, including cloud computing, big data and analytics, process automation, artificial intelligence / machine learning, and other digital strategies.
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The Center for Vision Technologies (CVT) develops and applies its algorithms and hardware to be able to see better with computational sensing, understand the scene using 2D/3D reasoning, understand and interact with humans using interactive intelligent systems, support teamwork through collaborative autonomy, mine big data with multi-modal data analytics and continuously learn through machine learning.
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Knowledge of one or more of the following technologies: Data Science, Machine Learning, Natural Language Processing, Business Intelligence, and Data Visualization. Design and maintain data structures for machine learning and other analytics.
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Proven track record as a Machine Learning Engineer with 4+ years of corporate experience in ML. Title: Machine Learning Engineer. Excellent knowledge of Machine Learning & Deep Learning domains.
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As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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Job Title: Machine Learning Engineer. Maintain Kubernetes pods, container registry and virtual machine image library and model registry. Implement best practices for security, data privacy and compliance in AI/Client workflows and infrastructure.
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Knowledge in at least four of: GitHub, DataBricks, FastAPI, Algorithms/Algorithm design, NLP, Machine Learning, Data Mining, Docker, Linux, Process Engineering, HuggingFace, Kubernetes, AzureDevOps.
$200,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated 10 days ago
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