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Requirements: Advanced degree (Ph. D. preferred) in a field like Applied Linguistics, Computational Linguistics, or Data Science, with a focus on building and deploying machine learning models for text analysis.
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AI and Machine Learning: Utilize state-of-the-art AI and machine learning techniques, including natural language processing (NLP), to train the chatbot for accurate and effective communication.
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Collaborate with data scientists and engineers to design, build, and maintain Azure-based MLOps pipelines for automating machine learning model deployment, monitoring, and maintenance. Implement Azure-based deployment pipelines for deploying machine learning models into production environments.
$135,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Bachelor's degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines and 5 or more years experience in predictive analytics or equivalent.
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The team uses emerging technologies and methods such as data fabric, machine learning, GenAI, NLP, computer vision, artificial intelligence automation, big data analytics, and cloud native application development to drive innovation, operational efficiency, and provide the data product excellence our customers have come to value and trust us for.
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Draw on deep technical knowledge and subject matter expertise to advise clients in multiple areas, including clinical psychology, psychiatry, neuroscience, and psychometrics, with an eye toward applications, such as digital mental health, psychological wellbeing, and predictive analytics and machine learning for personalized medicine and prevention.
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Reporting to the Director of Machine Learning Engineering the role requires a skilled Machine Learning Engineer to design, build, and deploy machine learning models that will help us derive actionable insights and solve complex problems.
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Requires three (3) years of experience in: (1) data analysis with Python and Python machine learning packages; (2) creating analytics tools to visualize KPIs in relation to equipment and process engineering; (3) MS Excel Macros and Pivot tables; (4) SQL, Tableau, and Spotfire; (5) knowledge of semiconductor process.
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Having experience with productizing machine learning models within a cloud service (e.g., AWS, Azure, GCP) and data science environments (e.g., Databricks) is a plus. You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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Join the Anheuser-Busch NAZ Tech Data and Analytics Team as a Machine Learning Engineer. Leverage data science frameworks like TensorFlow, PyTorch, and Spark ML to build robust and scalable machine learning solutions.
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2+ years of experience as a developer, data scientist or machine learning engineer in addition to 2+ years of experience in a TPM role Prior development or management experience on a Machine Learning Platform in a large tech company Hands-on experience with cloud technologies and service oriented architectures Track record of using data analytics for improving SW operations and organizational efficiency Advanced degree in an analytical field.
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In depth understanding of Machine Learning / Deep Learning / NLP concepts. Stay updated with the latest industry trends in AI and machine learning, and continuously look for opportunities to apply these advancements to improve the LLM infrastructure.
$144,000 - $270,250 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Data science, machine learning, optimization models, Master’s degree 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, Using open source frameworks (for example, scikit learn, tensorflow, torch)Doctorate, Masters: Artificial Intelligence.
$117,000 - $234,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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In this role, you will collaborate with researchers to develop machine learning methods for computational biology and drive the implementation and testing of novel research ideas using cutting-edge deep learning techniques.
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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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machine learning jobs Title: big Company: Booz Allen Hamilton
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