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Bonus if those were open-sourced big data processing frameworks using technologies like Spark, Airflow, Kafka, Flink, Iceberg, Deltalake. By integrating this data with our online systems, we empower multiple business lines, drive critical machine learning models, and fuel fast-paced experimentation.
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Minimum 2 years of experience with large-scale data processing platforms such as Spark, EMR, and/or HPC computing experience with e.g. Apache Aurora, Slurm. Helps grow and mentors team members on the fine art of data engineering and software abstractions.
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Focus on the development and application of new methodologies, technologies, and techniques to gather data and insights including machine learning AI, mobile optimization, gamification, behavioral economics, and virtual/augmented reality.
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The Data Capture team for the Data organization within the DE&ET organization is in search of a Lead Software Engineer. Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query.
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Work closely with the lead hardware engineer, electrical engineers, signal processing, mechanical, and test engineers, to convey sensor design architectural details, software message interactions process flows, software architectural design layout, hardware placement design, and firmware control interfaces.
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Experience with Databricks for data engineering, analytics, and machine learning. Utilize Databricks for data engineering, analytics, and machine learning tasks.
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Designs and builds data processing pipeline using cutting-edge AWS services, 3rd party open-source/commercial software, and internally developed software to ingest, process, and deliver data at scale.
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As a Systems Integration Engineer, you will be responsible for advancing several ongoing engineering and technology development projects related to creating web-based/cloud-based software/hardware interfaces for data and image analysis and to developing methods to perform computational post-processing on data.
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Python ecosystem preferred, R will be acceptable, machine learning libraries & frameworks (e.g. TensorFlow, PyTorch, scikit-learn) and familiar with data processing and visualization tools (e.g., SQL, Tableau, Power BI.
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Our primary developer offering is an ultra-performant Data Processing Framework (unified streaming + batch) with a Python API, distributed Rust engine, and capabilities for data source integration & transformation at scale (Kafka, S3, databases/CDC.
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We apply advanced technologies such as Digital Signal Processing, Analytics, Machine Learning, Artificial Intelligence, and Cloud computing to solve our customer and mission challenges.
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Knowledge of machine learning and AI methods and proficiency with scripting and executing data analytics algorithms and models with hands-on experience using a modeling and simulation software (e.g. Python, MATLAB, R, NONMEM, SAS, S-Plus, etc) is a must.
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In Disputes we build highly available and scalable, Machine Learning driven products that integrate with the broader Cash App ecosystem to help customers solve their problems. Your team will be responsible for one of three major work streams within the Disputes Team. You will work closely with the other work stream engineering teams, including Mobile Engineers, Product Managers, Designers and Machine Learning Engineers.
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Illustrative technologies or fields that the incumbent would be familiar with include big data, artificial intelligence/machine learning, open APIs, digital IDs, cloud computing, 5G, internet-of-things (IoT), distributed ledger technology, and others.
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The Data Science team at Meijer leads the strategy, development and integration of Machine Learning and Artificial Intelligence at Meijer. Build production ready prototypes for, and iteratively develop, end-to-end data science pipelines including custom algorithms, statistical models, machine learning and artificial intelligence functions to meet end user needs.
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machine learning software engineer data processing big jobs Company: Lyft
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