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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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We are seeking a highly motivated machine learning engineer to join our Imaging AI team in the Informatics and Predictive Sciences (IPS) organization. Principal Machine Learning Engineer, Imaging AI.
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Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. Spun out of Stanford in 2019, we have built an intelligent analytics platform fueled by our revolutionary device which uses machine perception and sensor fusion to provide an operations digital twin that combines factory operator activity with machine data for the first time.
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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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Conduct research and development of Natural Language Processing (NLP) models, and collaborate with engineers to bring these models into production. A graduate degree or equivalent in Machine Learning, Mathematics, Statistics, Physics, Economics, or a related technical field is preferred.
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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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Proven track record managing and scaling machine learning teams in one or more of the following areas: computational advertising, recommendation systems, risk/fraud modeling, autonomous vehicles, search, natural language processing, or a related field.
$216,000 - $378,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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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Data Processing and Feature Engineering: Develop pipelines and tools for data processing, feature engineering, and preprocessing to support machine learning model development.
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Work with the embedded Machine Learning Engineers on the team and ML platform services to deploy models to the production environment and monitor ongoing performanceUse Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP & AWS) to get the job doneQualificationsYou Have: 5+ years of Machine Learning modeling experience.
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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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QualificationsExperienceMust have at least one year of recent experience as an operating room technician surgical attendant anesthesia technician or central processing technician. Certification as a Central Processing Technician or Surgical Technologist required (CT SPT.
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Minimum of a Bachelor’s degree in Biology, Ecology, Environmental Science, Natural Resource Management, or a related life sciences field required. SWCA is expanding our natural resources team and seeking Assistant/Staff Biologist candidates for upcoming environmental projects involving a range of office and field duties throughout California.
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Our rapidly growing Industrial market encompasses a a broad range of projects that can span from Water/Wastewater treatment, Food & Beverage processing, Mineral Processing, Renewable Fuels, Pulp and Paper, Steel & Aluminum, Specialty chemical, Industrial Energy, Manufacturing, Automotive and Emerging Industrial Markets like EVBattery, Data Centers and Semiconductors.
$80,000 - $110,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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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. Accredited Artificial Intelligence (AI) / Machine Learning (ML) certifications (, AWS, Google Data Analytics, Microsoft Azure) Information for applicants with a need for accommodation: The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.
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machine learning natural processing jobs Title: engineer software in San Francisco, CA
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