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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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The position will be responsible for evaluating and creating cutting edge software and distributed computing infrastructure to support a range of application uses, ranging from machine learning for autonomous functions to fleet-data analysis empowering better mobility experiences for our customers.
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Come join Kohler Ventures as Sr. Embedded Firmware Engineer as we build a best-in-class global multi-disciplinary team across artificial intelligence, machine learning, design, advanced software and hardware engineering, strategy, venture investments, sales, marketing, and partnerships.
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BS, MS, or Ph. D. in Robotics, Machine Learning, Applied Mathematics, Computer Science or a related field. Our Learning and Development offerings include Aurora Academy, where our people learn, develop, and practice the essential skills that drive Aurora’s mission, continually up-leveling our team along the way.
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Design and build Machine Learning for capacity planning, demand forecasting, software performance analysis, and software system tuning. Develop Machine Learning models in the areas of Networking, Application, and Data. Design, write, and build software tools to improve the reliability, latency, availability, and scalability of Walmart eCommerce products.
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Building on this foundation, the organization will cultivate a top tier artificial intelligence & machine learning team focused on addressing complex problems that materially advance the drug discovery, development and delivery process.
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Hands-on experience with machine learning-related frameworks (e.g., TensorFlow, PyTorch, model registry, OpenMetadata, ML feature store). Solid theoretical background in machine learning or data mining and strong conceptual, problem-solving, and analytical skills.
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Frameworks for distributed machine-learning / AI, such as Azure OpenAI, AWS Bedrock or things like Tensorflow and MxNet. Our cloud-based Machinify AI platform leverages the latest advances in machine learning, large language models, data analytics, and cloud processing to solve previously intractable problems, transforming healthcare administration and payment operations.
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As a Software Engineer with Machine Learning (ML), you will support new and existing projects in the areas of GenAI in BigQuery, with a particular focus on building evaluation frameworks for new ML capabilities.
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Experience with Big data, machine learning, and numerical programming frameworks (e.g., TensorFlow, Python, MATLAB). Experience building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks.
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Proven experience as a Full Stack Machine Learning Engineer or similar role. Integrate machine learning models with cloud-based platforms and/or embedded systems for deployment in production environments.
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Lead end to-end deployment and maintenance of machine learning models in production, from concept, design, implementation, to rollout, ensuring the highest quality and performance. This position will be part of the Machine Learning Engineering and MLOps team support Global AI & Data Innovation.
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In this camp, we will take a multi-disciplinary approach to learning and incorporate studies in chemistry, oceanography, ecology, and marine biology to learn about Earth's amazing seas and the animals and plants that inhabit them.
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Coordinate equity-related programming and events, including workshops, seminars, and speaker series focused on cultural humility, cultural responsiveness, social-emotional learning, cultural capital and strengths-based learning, collaborate on creating equitable online learning resources and workshops, and sharing liberatory frameworks for teaching as well as relational pedagogies inside and beyond the classroom.
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Machine Learning / Deep Learning. - Expertise in machine learning infrastructure, including technologies like MLFlow, Kubeflow and large scale distributed systems. - Expertise in deep learning frameworks and tensor libraries like PyTorch, Tensorflow, JAX/FLAX.
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machine learning jobs Title: entry in Menlo Park, CA
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