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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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Deliver simple solutions to complex problems as a Machine Learning Engineer at GDIT. Here, you'll tailor cutting-edge solutions to the unique requirements of our clients. Education: Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree.
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As a Machine Learning Engineer at TRM Labs, you will collaborate with an experienced team of engineers, data scientists, and research scientists to build scalable systems to detect, prevent, and mitigate cryptocurrency fraud and financial crime.
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Deploy machine learning models and applications on cloud platforms like Azure ML or Databricks, ensuring seamless integration, scalability, and cost-effectiveness. Strong proficiency in developing machine learning models using Python machine learning packages, Azure Databricks, and other Azure technologies.
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Machine Learning and Deep Learning: Good understanding of: ML algorithms like linear regression, logistic regression, etc., supervised, unsupervised, and reinforcement learning, AI Frameworks like TensorFlow, PyTorch, scikit-learn etc., Neural network, NLP, computer vision, and predictive analytics.
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
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Bachelor’s degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field with 6+ years of professional experience in data science/machine learning.
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Boston, MA, Brooklyn, NY, San Francisco, CA, Washington, D.C., Remote, London, England 11-10-2023 HealthTech Azure Elasticsearch Docker AWS Python Machine Learning. 10+ years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions.
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As our first Data Science hire focusing on Machine Learning at Circle, you’ll start by focusing on two critical problems: helping identify transactions and actors who might be acting illicitly and helping us better balance our reserves across a series of accounts to reduce systemic risk inside the company.
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Machine learning libraries: TensorFlow, PyTorch, Scikit-learn , Deploying and optimizing different pipelines that support various data science processes. We are looking for candidate who can work without any sponsorship #W2 Machine Learning Engineer with 7+ years of experience in designing, building, and maintaining machine learning models and pipelines.
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The Fiduciary Officer is responsible for the efficient administration of Trust Accounts for FFB wealth management clients where the Bank is acting as trustee, executor, administrator, conservator, guardian or agent for Trustee.
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Train, tune and validate machine learning models using Tensorflow, python and GCP cloud infrastructure. Use techniques like LIME, SHAP, recent temporal pattern mining (RTP) to develop explainable machine learning models.
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Proven prior experience as a Machine Learning Engineer, Data Engineer, Software Engineer, or similar role. We are seeking an experienced Machine Learning Engineer (MLE) Manager to join our team.
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5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow, PyTorch and LangChain with GPU and CUDA experience being extremely advantageous.
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Extensive experience in at least one cloud platform (e.g. AWS, GCP, Azure) and associated machine learning services, e.g. Amazon SageMaker, Azure ML, Databricks. Support AAG leadership in extending and growing our machine learning, engineering and analytics capabilities.
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wealth management associate machine learning jobs Company: Jpmorgan Chase Co
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