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We work as a team: We are a collaborative company comprised of highly-educated industry leaders in radar systems, image and signal processing, machine learning, hardware development, and software engineering.
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Engage in the entire lifecycle of machine learning projects, from conceptualization and data processing to model development, deployment, and continuous optimization. Key Responsibilities:- Design, develop, and deploy advanced machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch and TensorFlow.
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Job Description Support GDIT's FedCiv business areas by developing solutions to deliver capabilities, focusing on Data Science, Machine Learning, and emerging artificial intelligence (AI) capabilities.
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Specifically, this experience must be in writing Big Data data engineering jobs for large-scale data integration in AWS; prior experience in writing Machine Learning data pipelines using Spark programming language is an added advantage.
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As a Machine Learning Engineer - Technical Lead II for Crowe Intelligent Document Analyzer (CIDA), you will design the future of this document extraction product as it transitions from a combination of Natural Language Processing and embeddings models to fully integrate with Crowe's in-house Generative AI platform and to leverage Large Language Models (LLMs.
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Our next-generation platform, which combines threat intelligence with machine learning, enables financial institutions and governments to detect cryptocurrency fraud and financial crime at an unprecedented scale.
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Ideal candidate would have at least 3 years of industry experience in the field of Artificial Intelligence, Machine Learning, and/or Cloud Computing. Kilpatrick Townsend’s Electronics & Software Patent Prosecution team seeks either a USPTO-registered Attorney or Patent Agent with a degree in Computer Science, Computer Engineering, or a closely related field.
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This may also include patent work related to image processing, databases, access management, natural language processing/understanding (NLP/NLU), and autonomous machines/vehicles. February 15, 2023 Location: Atlanta , Denver , Raleigh , San Diego , San Francisco , Seattle , Silicon Valley (Menlo Park) , Washington DC , Winston Salem Practice: (EES) Electronics & Software.
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As part of the Data Engineering team, you will work closely with business domain experts and data engineers to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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Learns about machine learning, data science, computer vision, artificial intelligence, statistics, and/or appliedmathematics as necessary to carry out role effectively. Partners with machine learning engineers, BI, and solutions architects to develop technical architectures forstrategic enterprise projects and initiatives.
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Collaborate closely with other engineering guilds to integrate machine learning components into larger software systems and develop end-to-end solutions. Join the Anheuser-Busch NAZ Tech Data and Analytics Team as a Machine Learning Engineer.
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You will work with a team of machine learning researchers to build AI software systems, learn about deep learning algorithms, and use your technical skills to advance autonomous driving.
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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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Responsibilities: Developing and training machine learning models using Natural Language Processing (NLP) techniques. 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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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges.
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machine learning software processing big jobs Company: Lyft
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