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You will deploy and deliver technical solutions at the intersection of computational chemistry and machine learning, supporting research directions in molecular design across broader gRED and Roche.
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Our team develops, implements, and maintains recommendation and personalization algorithms for Disney Streaming's suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.
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Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (e.g., AWS, Google Data Analytics, Microsoft Azure) Proficient with the core concepts of at least one programming language such as Python, R, and SQL and adept with machine learning frameworks such as TensorFlow and PySpark.
$229,500 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Continuously follow the advancement of machine learning and artificial intelligence to update your knowledge and skills in order to solve business problems with the most efficient methodologies.
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Clients in this practice group represent a diverse range of industries, including artificial intelligence and machine learning, autonomous vehicles, aviation, big data, cleantech and climate solutions, data storage, digital health and wellness, digital media and entertainment, electronic gaming, fintech, life sciences, robotics, semiconductors, software, and SaaS, and web3, among other emerging and disruptive technologies.
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We are particularly interested in candidates who are at the forefront of integrating artificial intelligence/machine learning into biology. The department is interested in recruiting new faculty who work at interfaces between scientific disciplines represented within our department (including computational biology, molecular engineering and design, therapeutic bioengineering, systems pharmacology, drug development sciences, pharmacogenomics) and across the entire discovery science community at UCSF (e.g. biochemistry, biophysics, cell biology, pharmacology, pharmaceutical chemistry, physiology, neuroscience, human genetics.
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Our machine learning systems monitor and surface suspicious activity (money laundering, illegal activity and terms of service violations) for agent review. Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performance.
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We are seeking a dynamic and experienced Principal Scientist specializing in AI and machine learning, with a Ph. D. in Machine Learning, Artificial Intelligence, Computer Science, Bioinformatics, or a related field.
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Proven experience with enterprise-scale technical delivery experience with AI Services including OpenAI, Schematic Kernel, AWS Bedrock, Machine Learning (or equivalent), Generative AI, LLM customization, NLP, Search, MLOps, Open-source AI frameworks, AI Infrastructure, architecture designAbility to align AI/ML initiatives with broader business goals and outcomes, understanding how AI can drive value and competitive advantage.
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The incumbent will apply advanced data analysis skills and machine learning in collaboration with a group of computational and biological scientists to perform translational oncology research around multimodal translational data sets for programs in clinical development.
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Determine how to leverage data science, machine learning, and other analytical techniques to offer actionable insights both internally & externally. Extensive experience with business intelligence tools, such as Tableau and Looker.
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Apply mathematical (geometry, linear algebra, numerical methods, error analysis) and machine learning methods to prototype and develop algorithms for converting raw depth sensor data into point clouds, 2D and 3D tracking like SLAM, 3D point cloud reconstruction, registration, and classification as well as texture projection and completion.
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Experience with cloud platforms such as AWS, Azure, or Google Cloud, and proficiency in using relevant tools and services for deep learning development and deployment. Model Deployment: Architect scalable and reliable deep learning pipelines for deployment in production environments, collaborating with DevOps engineers to ensure seamless integration and monitoring.
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Candidates should be familiar with some of the following: subsurface imaging with passive seismic data, geomechanics, earthquake characterization, seismicity forecasting, seismic wave physics, big data processing, machine-learning-based processing, distributed fiber optic sensing, seismic sensors and deployment, hydraulic fracturing, and/or geothermal exploration.
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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics. At a minimum, you should be able to implement and optimize deep learning algorithms developed by others.
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deployment machine learning intelligence jobs Company: Jpmorgan Chase Co in San Francisco, CA
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