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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
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Expertise in machine learning frameworks, including TensorFlow or PyTorch, and the ability to leverage them for custom solutions. A minimum of 6 years of experience in designing and implementing complex AI and ML solutions, as a Senior Data scientist, Machine Learning Engineer, or AI Engineer.
Full-timeRemoteExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed AI components.
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Understanding of machine learning algorithms (e.g. k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests), statistical analysis, and data visualization techniques; Staying current with the latest advancements in data science and machine learning.
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Deep Learning and Machine Learning using frameworks, such as TensorFlow or PyTorch etc. Foster a culture of learning and innovation. Cultivates Csuite relationships with global cloud service providers (CSPs), digital services/SaaS providers, enterprise, cloud and public sector customers, independent software vendors (ISVs), system integrators (SIs), and managed service provider (MSP) partners to maximize utilization of Company product capabilities.
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Experience with Machine Learning and related technologies such as Tensorflow Python, Torch, Amazon SageMaker, Jupiter Notebooks, git. Possess deep functional and technical understanding of the Machine Learning technologies (Google’s Cloud Platform, custom and COTS-embedded) and provide prescriptive guidance on how these are leveraged across the Fuse landscape.
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Machine Learning Frameworks - Exposure to at least one machine learning framework or library, such as scikit-learn, TensorFlow, or PyTorch. · Fundamental Concepts of AI and Machine Learning - Basic understanding of key concepts and terminologies in artificial intelligence and machine learning, such as supervised and unsupervised learning, neural networks, and deep learning.
$40,000 - $50,000 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Understanding of Azure stack like Azure Machine Learning, Azure Data Factory, Azure Databricks, Azure Kubernetes Service, Azure Monitor etc. Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Bias, Business, Coaching, Creativity, Critical Thinking, Cybersecurity, Data Analysis Management, Data Collection Management, Data Controls, Design Thinking, Development Methodologies, Empathy, Follow-Through, Growth Mindset, Implementation Methodologies, Infrastructure Design, Intellectual Curiosity, Long Term Planning, Managing Ambiguity {+ 4 more.
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Proficiency in Python and familiarity with key data science and machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Transaction Network Services (TNS), a subsidiary of Koch Industries, is seeking a skilled Senior Data Scientist to join our AI Labs. This role involves analyzing complex datasets, developing statistical and deep learning models, and implementing advanced machine learning solutions.
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Familiarity with at least one machine learning / deep learning framework (e.g., tensorflow, pytorch). The LINC project brings together a multi-disciplinary group of experts from 8 institutions (Brigham and Women’s Hospital, Columbia University, Harvard University, Massachusetts General Hospital, Massachusetts Institute of Technology, University College London, University of Rochester, Weill Cornell Medicine) to develop novel imaging technologies and combine them with machine learning to produce detailed wiring diagrams of the brain.
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Optimize machine learning algorithms and infrastructure for performance, scalability, and cost-efficiency. Deploy machine learning models into production environments, ensuring scalability, reliability, and real-time performance.
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Staff Machine Learning Engineer (Remote within Ireland) As a Staff Machine Learning Engineer on the Predictive AI Models team at HubSpot, you’ll do many things— and you likely already have experience doing some of them in the past.
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Founded in 2011, we have a long history of delivering tech-forward web/cloud, robotic, IoT, and machine learning solutions. Breadth of Experience (e.g., Full Stack Web experience, Machine Learning expertise, Python mastery, etc.
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Machine learning packages (PyTorch, Tensorflow, etc.) Proven understanding and professional experience applying machine learning/deep learning concepts and techniques such as random forest, support vector machines, RNNs, CNNs, LSTM, etc.
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Experience with building machine/deep learning models with at least one common framework such as PyTorch, Tensorflow, or JAX. As a Machine Learning / Artificial Intelligence (ML/AI) Engineer on Ginkgo’s Design Team, you will leverage Ginkgo’s wealth of proprietary sequence and experimental data to design, train, and experimentally validate novel foundation and application-specific ( e.g. fine-tuned) AI models for application to classification and design of genes, regulatory elements, multi-gene pathways, and even genomes.
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