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Programs on 5G, quantum computing, artificial intelligence, deep learning, quantum computing and from artificial intelligence and deep learning to cyber. programs on 5G, quantum computing, artificial intelligence, deep learning.
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Have expertise in Machine Learning best practices (e.g. model evaluation and hyperparameter tuning, A/B test, feature engineering, feature/model selection), algorithms (e.g. gradient boosted trees, neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization and recommendation, anomaly detection.
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5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful.
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As a machine learning engineer, you’ll have the opportunity to immediately drive a huge, direct impact for Propel! Lead Propel in building machine learning infrastructure that all teams can take advantage of.
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We are seeking a skilled Machine Learning Engineer with expertise in Azure, Databricks, and MLflow, as well as strong full-stack capabilities, including experience with React. Experience with Azure cloud services, particularly Azure Machine Learning and Azure Databricks.
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Provide technical expertise and support to POD teams in the development and implementation of machine learning and AI solutions, leveraging Azure, Databricks, and MLflow. As a Machine Learning Engineer supporting POD teams, you will play a pivotal role in providing technical expertise and guidance to ensure the successful development and delivery of machine learning and AI solutions.
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5+ years of experience in machine learning engineering, data science, or a related field. Your responsibilities will include collaborating closely with product teams, contributing your expertise in machine learning technologies, and leveraging your full-stack capabilities to support the implementation of frontend components using React.
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You will identify and address an applied machine learning problem in the enterprise co-pilot system, working with ML Engineers across the organization to adopt and productionize LLM usage.
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Innovative Refrigeration Systems is looking to hire a Lead Machine Learning Engineer full-time onsite in Waynesboro, VA. You would be joining our software engineering department to build machine-learning models optimizing energy efficiency for heavy industrial refrigeration / cold storage facilities.
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Assist in the deployment of machine learning models into production environments, implementing monitoring and logging mechanisms for performance tracking. Collaborate with frontend developers to support the implementation of responsive and user-friendly web interfaces using React, integrating machine learning capabilities seamlessly into frontend applications.
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Knowledge of machine learning algorithms, statistical modeling, and data structures. Assist in the development and optimization of machine learning algorithms and models, providing guidance on best practices and methodologies.
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Proficiency in Python for machine learning and data analysis. Strong problem-solving mindset and a proactive attitude towards learning and self-improvement. Document technical solutions, processes, and best practices, and share knowledge with team members to facilitate learning and collaboration.
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We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. This role is based remotely but if you live within a 50-mile radius of Warren, MI, or Austin, TX, you are expected to report to that location three times a week, at minimum.
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GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) Experience with version control systems (e.g., Git) and containerization technologies (e.g., Docker) is desirable.
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We are seeking a highly motivated machine learning and AI Principal Scientist to join our Computational Tissue Imaging Research team in the Translational Bioinformatics organization. Strong coding skills in Python, and experience with machine-learning and deep learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, etc.
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Title: machine learning researcher Company: Global Leading Market Maker
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