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Train, tune and validate machine learning models using Tensorflow, python and GCP cloud infrastructure. Knowledge of programming and machine learning tools including Python, SciPy/NumPy/Pandas, TensorFlow, Git and cloud computing platforms.
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Senior Machine Learning Engineer AtanAI Boston, MA, Brooklyn, NY, San Francisco, CA, Washington, D.C., Remote, London, England 11-10-2023 HealthTech Azure Elasticsearch Docker AWS Python Machine Learning.
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More Full Time Jobs Lead Machine Learning Engineer Mountain View. Experience working with cloud-based data warehouses like Snowflake, Redshift, or BigQuery. Working with dbt, Snowflake, Airflow, Python, Stitch, and git, and we welcome new ideas.
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You will develop robust and scalable data pipelines, ML model hosting, and backend services for enterprise line of business applications in Python, VertexAI, Airflow, dbt, Flask, PostgreSQL, BigQuery, Docker, Kubernetes, and more.
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Utilize Databricks for big data processing, analytics, and machine learning workflows. Optimize data processing and query performance for large-scale datasets within Azure and Databricks environments.
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Apply statistical and machine learning methods to solve large scale problems, including the full modeling lifecycle (e.g. data manipulation, building and evaluating models, interpreting and effectively communicating results, transitioning solutions to production, performance monitoring, recalibrating models, etc.
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PhD in a field relevant to biomedical research (bioinformatics, biomedical engineering), or computer science (computer science, machine learning, artificial intelligence) or similar. The Bioinformatics Programmer/Data Scientist will assist in managing, cleaning, and analyzing large scale medical data using a wide variety of analytic techniques, both in the cloud and with on-premises compute depending on data permissions.
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5+ years of experience as a Machine Learning engineer building production-level pre/post-processing data pipelines for ML/DL modelExperience in statistical analysis & visualization on datasets using SQL, Pandas or R.
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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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Scale cutting-edge model techniques to Cash App’s huge volume of data. 5+ years experience with applied Machine Learning or Deep Learning. Machine Learning is at the heart of our automation approach, and we are looking for a senior modeler to lead our automation efforts across new Support surfaces.
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Working closely with our data engineering team, you'll design an implement an enterprise-grade machine learning infrastructure focused on credit risk modeling and fraud detection based on blockchain data.
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We're hiring generalist software engineers to work on web applications, data mining, machine learning/data science, data transformation/ETL, data modeling, database scaling, infrastructure, devops, and more.
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Senior Software Engineer with backend / distributed systems / large scale and database/data processing or data streaming centric background and coding skills in at least one of Go, Golang, Python, Java or C.
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An advanced degree in computer science, data science, machine learning, artificial intelligence, operations research, engineering, or related quantitative discipline. Experience developing and operating large-scale data pipelines demonstrating knowledge with technologies, such as Airflow, Luigi, Spark, Kafka, ElasticSearch, Cassandra, RDBMS and SQL.
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This role is part of our Cash App R&D team which sits within our Machine Learning and Data Science organization. Engage in the creation of experiments, prototyping, and architectural design, contributing to a diverse range of computer science domains such as machine learning, data mining, natural language processing, and performance analysis.
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