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Analyze and parse data in a variety of geospatial file formats and databases for machine learning and algorithm optimization, testing, and validation. Master's or PhD degree in STEM field (Electrical Engineering, Physics, Computer Engineering, Remote Sensing, or another relevant technical field.
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PhD degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Mathematics, Statistics or a related field; coursework or academic research to include image identification or artificial intelligence.
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PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields. PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series.
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A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
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Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
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Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money.
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PhD Computer Science, Mathematics, Statistics, Physics, Linguistics or a related field with a dissertation, thesis or final project centered in Machine Learning and Deep Learning) with 2+ years relevant experience is preferred but not a must; OR.
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The Lytx Labs Team develops machine learning and computer vision algorithms to monitor and assess the state of drivers and their environment to identify risk and improve safety for our clients.
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For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model.
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MS/PhD degree or equivalent practical experience in Computer Science, AI, Machine Learning, or related technical fieldStrong understanding of ML techniques such as CNNs, supervised and unsupervised learning, optimization techniques, etcExperience with one or more of popular Deep Learning frameworks such as Caffe, TensorFlow, TheanoExperience in a fast-paced work environment, shipping quality code quickly and iteratingWhat We Offer.
$500,000 - $1,000,000 a yearExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Researching and identifying Artificial Intelligence (AI) methods – including Machine Learning (ML) and Natural Language Processing (NLP) methods. A Master's degree or PhD in a quantitative field (e.g., statistics, computer science, mathematics physical/biological sciences, or GIS.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Architects the underlying operating system, core services, platform infrastructure, dev toolkits, core algorithms, machine learning models, packaged end-user apps, and app store marketplace.
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PhD focus on NLP or Masters with 10 years of industrial NLP research experience. Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems.
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Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is embarking on the most transformative change to its business and technology in company history, and our Machine Learning Engineers are at the forefront of this evolution.
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