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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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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 Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow based tools, data platform and cloud services (both GCP & AWS) to get the job done Qualifications You Have: 5+ years of Machine Learning modeling experience.
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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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Modeling : Apply state of the art machine learning and statistical analysis to develop models related to opportunity sizing, targeting, and optimization. ~3+ years related experience with developing machine learning models and conducting statistical analysis.
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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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Experience with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure, and familiarity with cloud services for machine learning (e.g., SageMaker, AI Platform, Azure ML.
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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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San Francisco, California (Hybrid On-Site): $248,700 - $283,800 for Sr. Lead Machine Learning Engineer. New York City (Hybrid On-Site): $234,700 - $267,900 for Sr. Lead Machine Learning Engineer.
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It will involve close collaboration with computational scientists from a diverse range of disciplines, including molecular modeling, computational biology, discrete simulation, machine learning, and artificial intelligence.
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Skilled in learning design Bloom taxonomy) and measurement Kirkpatrick framework), enablement tooling (Learning management, content management, and Articulate/RISE), gamification, and program management across multiple stakeholders “master herder of cats.
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Experience in applying Client analytical or computational (machine learning) technique and data science expertise to integrate and mine large complex data is a plus. Qualifications:· Candidates should have a doctoral degree in bioinformatics, computational biology, statistics, data science, other relevant fields with at least 1-3 years/ master’s degree with at least 5-7 years/BS degree with at least 10 years of relevant post-degree experience, preferably in pharma/biotech or related research organizations/academia.
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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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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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Drive and execute on delivering market intelligence and customer insights for enterprise robotics, embodied AI, simulation and machine learning workloads. BASIC QUALIFICATIONS- 5+ years experience related to business development, management consulting, strategic partnerships, enterprise sales, technology development, or program/product management experience.
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Position InformationCurriculum Development and Assessment Plan Prepare and implement learning activities that are in alignment with the center’s philosophy;Meet program curriculum goals, reflect children’s abilities, interests and skills, are in alignment with the National Association for the Education of Young Children’s (NAEYC) best practices;Implements inquiry-based teaching, Reggio Emilia philosophy, and the California Department of Education for Early Learning.
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sales machine learning jobs Company: Axtria Inc in South San Francisco, CA
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