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As a Machine Learning Engineer at Nelnet, you'll be at the intersection of data science and software engineering. Our Machine Learning Engineer role is at the core of this transformation, creating intelligent systems that automate processes, derive insights, and enable us to make better decisions.
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As a Machine Learning Engineer, youll develop ML-based metrics for evaluating an autonomous vehicle system offline at large scale. Machine Learning development experience. As a Machine Learning Engineer, youll develop ML-based metrics for evaluating an autonomous vehicle system offline at large scale.
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Additional experience with Pyspark, AWS S3, Lambda, EC2/AZ, Data bricks, Machine learning (ML), GenAI/ Computer Vision, Theory of Probability, GitLab, R Programming, GCP & Airflow will be preferred.
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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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The world of healthcare is changing fast and Commonwealth Radiology Associates is the “tip of the spear” when talking about advancements in Diagnostic Modalities, Image-Guided Intervention, AI, Machine Learning, and Health Blockchain Technology.
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Massachusetts General Hospital (MGH) Department of Neurology and Harvard Medical School (HMS) is seeking a signal processing and machine learning post-doctoral fellow for a full-time position in the Gupta Lab. The fellow will be applying diverse methodologies to uncover information in multimodal data collected from individuals with common and rare neurodegenerative diseases.
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Programming skills, signal processing, machine learning, and/or deep learning are highly welcome. Please send your application materials to Dr. Shahab Haghayegh at shaghayegh@mgh.harvard.edu and Dr. Lei Gao at lgao@mgh.harvard.edu.
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Experience with neural deep learning methods and machine learning. Machine learning (ML) has been strategic to Amazon from the early years. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.
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Evaluates and recommends: upcoming industry trends, best practices, cutting-edge tools and novel programming approaches that leverage machine learning, simulation, robotic automation, metadata driven processes, artificial intelligence and natural language processing.
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Keywords: Cheminformatics, Computational Chemistry, Machine Learning, Artificial Intelligence, Computational Sciences, Drug Discovery, Pharmaceutical, Biotechnology, Boston, Cambridge, Massachusetts.
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Familiarity with popular machine learning/deep learning/statistical packages (such as scikit-learn, TensorFlow, PyTorch, etc.) Experience and understanding of modern CI/CD DevOps and orchestration tools such as Azure DevOps, Airflow, Kubernetes and Docker.
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Stay abreast of the latest advancements in AI, machine learning, and computational biology, and apply these insights to drive the company’s research agenda. As the Principal Machine Learning Scientist, you will be the driving force behind the AI initiatives that propel the company’s innovative drug discovery platform.
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Experience working with digital educational content or designing learning experiences as an instructional designer, a learning experience designer, a creative role in ed tech, in educational publishing, or with experimental pedagogical approaches in the classroom.
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Whether it’s holding a PhD-level deep dive into understanding fairness and underlying bias in machine learning models, debating the merits of a Scandinavian design philosophy in our UI/UX, or writing responses for Medicare rules to influence U.S. health policy, we prioritize sharing our findings across the team and helping each other be successful.
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Familiarity with machine learning libraries such as scikit-learn, Tensorflow, PyTorch, Keras, etc. A minimum of 2 years of industry or research experience in signal processing and/or machine learning.
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machine learning jobs Company: Gradient Ai in Boston, Papillion, Nebraska
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