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Cellular 4G/5G Firmware Data Science & Machine Learning Engineer. Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse substantial data and logs in a timely manner to automatically tackle the issues or provide recommendations for the next step of solving problems.
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Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, monitoring, and feedback loop. Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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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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Job Description :We are looking for a seasoned Machine Learning Engineer specialized in Large Language Models (LLMs) to drive the development and deployment of cutting-edge AI solutions.
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Engage in continuous learning to stay abreast of the latest developments in mobile health technology, data science, and machine learning. ⢠Develop on-device data visualization and machine learning models for personalized feedback and adaptive interventions.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics.
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Knowledge of DevOps practices and continuous integration/continuous deployment (CI/CD) pipelines Familiarity with the AWS cloud platform Previous experience in the deployment of machine learning models in production environments.
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Overview Are you a a data expert with broad understanding and experience in solving business problems by integrating statistical analysis, machine learning/artificial intelligence, deep learning, Natural Language Processing (NLP) and Large Language Models (LLMs.
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Additionally, you will collaborate with teammates and platform teams to develop ML tooling and infrastructure for scalability. Our platform does what legacy observability and monitoring tools can’t: we eliminate the gaps between system performance, user experience, and engagement, enabling issue identification, impact assessment, and root cause resolution in seconds.
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Proven experience as an NLP Engineer, Machine Learning Engineer, or similar role, with a strong background in natural language processing and machine learning. Machine Learning and Deep Learning: Utilize machine learning frameworks (e.g., TensorFlow, PyTorch) to train and optimize NLP models.
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The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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Experience building loan-level credit/prepayment models from data preparation, data analysis, and model estimation through deployment into productionExperience with generalized regression models as well as machine learning frameworksVery strong programming and software design skills (Python, C.
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3 years industrial experience in Machine Learning, Artificial Intelligence AI/ML, Deep Learning, Cloud Computing, Applications Development, Cybersecurity, IT, Computer Science, System Support, Databases/Fulfillment, Storage, Electrical Systems, Software Design/Development, Programming or Robotics required.
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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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Knowledge of data science, machine learning, and artificial intelligence is required. Knowledge of data science, artificial intelligence, and/or machine learning is required.
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deployment machine learning jobs Title: platform Company: Baird
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