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The “Winning with Data” (WWD) capability in AbbVie’s International Commercial Business is driving the transformation of the organization into a data driven decision-making organization and is seeking an experienced and talented Machine Learning Operations Engineer to join our team.
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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications within The Friedkin Group of companies. Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP.
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We are seeking a highly motivated Machine Learning Engineer Co-Op from July 2024 to December 2024, focusing on Natural Language Processing (NLP) and Computer Vision applications. 2024 Fall Co-Op - Machine Learning Engineer (NLP & Vision.
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The Machine Learning Engineer, Sr. will be a key member of the Learning and Active Perception (LEAP) group in AV’s MacCready Works division and lead the development of a variety of innovative computer vision detection, classification, localization, and tracking solutions for defense and commercial applications.
$149,760 - $224,640 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Optimize machine learning algorithms and infrastructure for performance, scalability, and cost-efficiency. Deploy machine learning models into production environments, ensuring scalability, reliability, and real-time performance.
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We are looking for 3 to 5 years of experienced Machine Learning Engineer with a strong background in data science, machine learning (ML), Natural Language Processing (NLP), and Large Language Models (LLM) technology.
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Senior Machine Learning Engineer, Runtime & Optimization. Experience in developing on or using deep learning frameworks (e.g., PyTorch, TensorFlow, ONNX, etc.) These efforts have resulted in making machine learning more accessible to teams at Waymo, including Perception, Behavior Prediction, Planner, Maps and Research, ensuring greater degrees of consistency and repeatability, and addressing the "last mile" of getting models into production and managing them once they are in place.
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Extensive experience with scientific libraries in Python (numba, pandas) and machine learning tools and frameworks (scikit-learn, tensorflow, torch, etc. Develop tools and processes for automatically train, updating and evaluate LLM (Large Language Models)Qualifications: Strong foundation in Machine Learning (ML), Deep Learning, LLMs and NLP Hands-on experience in applying Natural Language Processing solutions to challenging real-world problems.
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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. Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in Springfield, VA or St. Louis, MO.
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Hands-on experience of machine learning methodologies including advanced analytics tools (such as R and Python) along with applied mathematics, ML and Deep Learning frameworks and libraries (TensorFlow, PyTorch, Keras) and ML techniques.
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As a Machine Learning Engineer you will help ensure today is safe and tomorrow is smarter. · Demonstrated professional or academic experience with deep learning frameworks such as PyTorch or Tensorflow to optimize convolutional neural networks (CNN) such as ResNet or U-Net for object detection or segmentation tasks using satellite imagery.
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Join our team as a Machine Learning Engineer, where you will play a pivotal role in leveraging data-driven solutions to drive innovation and business impact. Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and experience deploying machine learning models using containerization technologies (e.g., Docker, Kubernetes.
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The Machine Learning Engineer is responsible for proposing, planning, executing, and analyzing research and development machine learning projects related to the field of advanced manufacturing artificial intelligence.
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We are currently sourcing for a Lead Software Engineer, Machine Learning to work at Fidelity Investments. As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines.
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Proficiency in Google Cloud Platform (GCP) services relevant to machine learning and AI, such as AI Platform, BigQuery, Dataflow, and Tensorflow. Experience with building and training machine learning models using tools like TensorFlow, Keras, or PyTorch.
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