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As a member of the Auto Analytics State Deep Dive team within Personal Lines Auto State Analytics, you will play a critical role in developing, monitoring, and evaluating strategies and tactics for the PL Auto book to accomplish profitable growth in our large complex states.
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With a recent grant from the Massachusetts Life Science center, the Division has built the Lab for AI/Deep Learning for the Microbiome, which has a state-of-the-art GPU cluster for model development, training and deployment.
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Proficiency in Python, and experience with deep learning libraries/frameworks (TensorFlow, PyTorch) Develop and implement state-of-the-art deep learning models leveraging transformer architectures applied to massive semi-structured text from job profiles (resumes, job postings, performance reviews, etc.
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Experience with deep learning libraries and frameworks (TensorFlow, PyTorch, Langchain, ) This role serves as the most senior deep learning researcher role in the company, reporting to the CTO. They will be in charge of identifying technology gaps, defining research plans, and executing plans with an efficient research team.
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2+ years of industry experience in supporting the development of production-ready solutions leveraging AI technologies: NLP, Deep Learning, Machine Learning. Experience with deep learning frameworks such as TensorFlow, Keras, PyTorch, Transformers.
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This role will be part of a team of 4 and report to the Auto Analytics State Deep Dive Actuarial Manager. Develop a deep understanding of the assigned states in various aspects that contributed to the success of the whole state operations and underwriting economics, pursuing ad-hoc projects as needed to help support evaluation of state levers.
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Expertise in deep learning-based object detection, multiple object tracking, data association, and representation learning (detection points, heatmaps, and raw radar waveforms) is required. Research Areas: Artificial Intelligence, Computational Sensing, Computer Vision, Dynamical Systems, Machine Learning, Optimization, Signal Processing.
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A Deep Brain Stimulation device sends electrical signals within the brain that can help reduce symptoms of certain disorders or disease. In addition to Base Salary, this position is eligible for a Sales Incentive Plan (SIP), which provides the opportunity to earn significant incentive compensation for achieving or exceeding your goals.
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We're looking for dedicated individuals who take pride in their work and strive for excellence in ensuring the safety and well-being of our patients and staff.
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Design and implement deep-learning (DL) and machine-learning (ML) models to extract valuable insights from large repositories of time-series/biosensor data. This position is with the Signal Processing team at WHOOP. As a Signal Processing Engineer, focused on Deep Learning, you will be part of a cross-functional team composed of Signal Processing, WHOOP Labs, Firmware, and Data Science.
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Wolters Kluwer combines deep domain knowledge with specialized technology. Professionals in healthcare, legal, business, tax, accounting, finance, audit, risk and compliance rely on Wolters Kluwer's market-leading information-enabled tools and software solutions to manage their business efficiently and deliver results to their clients and succeed in an ever more dynamic world.
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Deep Learning Data Science Manager. 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms.
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Experiment with various deep learning architectures, hyperparameters, and data augmentation techniques to improve model performance. Proven experience in developing deep learning models, with a strong focus on transformers, retrieval augmented generation, and/or reinforcement learning.
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