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Technical Acumen:Perform model training and validation using various types of machine learning techniques on structured/unstructured data, including imagery, text and graphs. Technical Oversight:Provide technical guidance on model training and validation using various machine learning techniques on structured/unstructured data, including imagery, text, and graphs.
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The Opportunity As a Computer Scientist/Engineer on the Fraud Team, you will be at the forefront of developing and executing an innovative strategy utilizing Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Large Language Models (LLM), and Multi-Agent Systems to combat a variety of fraudulent activities.
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We are expanding in data science to provide the best information possible utilizing the latest techniques in Machine Learning (including Deep Learning, Neural network.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture design.
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Research and education areas at DIMACS include algorithms, combinatorics, complexity, privacy and security, discrete and computational geometry, optimization, graph theory, data science, artificial intelligence, and machine learning, with applications in sustainability, epidemiology, genetics, networks, transportation, security, and economics.
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Preferred Qualifications: 2+ years of experience as a developer, data scientist or machine learning engineer in addition to 2+ years of experience in a TPM role Prior development or management experience on a Machine Learning Platform in a large tech company Hands-on experience with cloud technologies and service oriented architectures Track record of using data analytics for improving SW operations and organizational efficiency Advanced degree in an analytical field.
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We are a well established Defense contractor with deep expertise in Machine Learning and Deep Learning projects for Military and Homeland Security programs. Defense industry leader in Machine Learning/Deep Learning programs - we are hiring for multiple roles in our Los Angeles HQ.
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4- 8 years of experience as machine learning engineer/data scientist. Aggregate huge amounts of data and information from large numbers of sources to discover patterns and features necessary to build machine learning models for prediction and forecasting.
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Experience with cloud platforms such as AWS, Azure, or GCP. Familiarity with machine learning concepts and frameworks is a plus. NOTE: THIS POSITION IS TO JOIN AS W2 ONLY. Data Engineer with Databricks Location: Remote Duration: 6+ Months Daily Responsibilities: Design, develop, test, deploy, maintain, and improve software applications and services.
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You: As a Machine Learning Compiler Engineer II on the AWS Neuron Compiler team, you will be supporting the ground-up development and scaling of a compiler to handle the world's largest ML workloads.
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Through our commitment to rigorous academics, social-emotional learning, deep family and community engagement, and health and wellness, we create lifelong learners who are equipped to fulfill their vision of success in and out of the classroom.
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Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax. Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture designAbility to align AI/ML initiatives with broader business goals and outcomes, understanding how AI can drive value and competitive advantage.
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Process data and information at massive scale as an Artificial Intelligence (AI) and Machine Learning (ML) Engineer with machine learning technologies. Experience with conducting research and the implementation of the latest advancements in machine learning to analyze and process large-scale spatio-temporal data.
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Machine Learning and Deep Learning: Utilize machine learning frameworks (e.g., TensorFlow, PyTorch) to train and optimize NLP models. Hands-on experience in NLP algorithm development, machine learning, and deep learning for text analysis and processing.
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machine learning deep jobs Title: data engineer Company: Nova Ltd
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