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As a Senior Machine Learning Engineer, You Will Be Building a Platform That Accelerates Drug Discovery With Machine Learning For a Wide Variety Of Use Cases With Respect To Data Modality, Model Architecture, And Model Size. By Leveraging Your Experience In Machine Learning, Software Engineering, Infrastructure, And Data, You Will.
$170,000 - $192,000 a yearFull-timeExpandUpdated Today - UpvoteDownvoteShare Job
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Proven ability to Formulate data science and machine learning strategies to align with business objectives. Apply your skills with Databricks, using Python, and big data streaming to pioneer client technologies and data.
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Data science, machine learning, optimization models, Master's degree 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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The Computational Biology group in the Clinical Biomarkers & Diagnostics (CBD) department at Company is seeking a highly motivated Sr data scientist to join our team and contribute to develop machine learning modeling and prediction pipelines using multi-modal biomarker data from clinical trials.
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Stay up-to-date with the latest trends and technologies in MLOps and data visualization, specifically related to autonomous driving perception and machine learning. In this role, you will work closely with Machine Learning (ML) engineers, data scientists, and software engineers to build scalable and high-performance applications that enable ML engineers to efficiently curate and build model training datasets, as well as evaluate their models across petabytes of multimodal data.
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Data Science / Machine Learning => 5/10 experience. You will design, develop, test, deploy, and maintain distributed & GPU-enabled Machine Learning Pipelines using K8s/AKS based Argo Workflow Orchestration solutions, while collaborating with Data Scientists.
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Experiences in data science and building and evaluating large scale machine learning & deep learning models. We are seeking phenomenal Data scientists and Applied Machine Learning engineers to support our Personalization and Item Recommendation development efforts with our eCommerce team.
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Kubernetes, Azure, Python, Data Science/ML. Enable/Support platform to do distributed data processing using Apache Spark and other distributed / scale technologies. Dexian is seeking a Machine Learning Engineer/AI Engineer for an opportunity with a client located in San Francisco, CA.
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Min Requirements: 7 years' experience in data science, machine learning, optimization models, or related field. This isn't analyst work; you'll be leveraging data science methods, including AI and machine learning in an incredibly dynamic and engaging environment.
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As a Machine Learning Engineer, build and maintain large scale ML Infrastructure and ML pipelines. You are familiar with applied data science methods, feature engineering and machine learning algorithms.
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Large scale machine learning & deep learning models. Machine Learning, Statistics, Personalization and Item Recommendation algorithms. Design, implement and own the state of the art Machine Learning approaches including.
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We are seeking a highly skilled and motivated Senior Applied Machine Learning Engineer for our Federal Delivery team who is passionate about delivering value to US Federal Government clients with Generative AI. If you have experience harnessing data to deliver mission impact at enterprise scale, enjoy working with alongside product teams to iteratively improve capabilities, and thrive in client-facing technical environments, we would love to hear from you.
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6+ years of professional development experience as Machine Learning Engineer, Data Scientist or related role 6+ years of programming experience with modern languages such as Python, R, C#, Java, or Scala.
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Design, implement and own the state of the art Machine Learning approaches including deep learning, reinforcement learning, and computer vision techniques. Expertise in Machine Learning, Statistics, Personalization and Item Recommendation algorithms.
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Machine Learning, Personalization and Recommendation Systems. deep learning, reinforcement learning, and computer vision techniques. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.
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