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Join the Anheuser-Busch NAZ Tech Data and Analytics Team as a Machine Learning Engineer. Leverage data science frameworks like TensorFlow, PyTorch, and Spark ML to build robust and scalable machine learning solutions.
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Plasma torch machine, natural gas/oxygen torch, carbon arc gouging rods and machine, welding machine, welding jack, welding shield or curtains, air/electric surface grinders, air/electric cone grinders, air powered chipping hammers, chisels, drifts, air/electric hoists, castings manipulators, shovel, broom, wheelbarrow, adjustable wrench, electric conveyors, forklift, overhead crane, de-slagging hammer, wire brush, miscellaneous handheld tools, gauges, shims, etc.
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Performing pat down searches, operating an x-ray machine, screening baggage, and reviewing tickets. At least one year of full-time work experience in security work, aviation screener work, or X-ray technician work.
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The Sewing Machine Operator will be working with the production team to ensure the manufacturing process is completed in a timely manner. The Sewing Machine Operator will be accountable for the following but not limited to just these responsibilities.
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Skil in operating all floor cleaning equipment which includes floor buffer/burnishes, water extraction machine, and carpet cleaning equipment. The floor technician may be responsible for cleaning and maintaining floors, including stripping, scrubbing, buffing, waxing, refinishing, sealing, and spot cleaning.
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Operate pavement grinders, asphalt curb machines, paint machine, sign machine, post puller, and post remover. What you will be doing: Drive and operate all Street Department equipment including front end loader, backhoe, skid loader, tandem truck, bucket truck, dump trucks, salt spreaders, snow plows, pickup trucks, street sweeper, stump grinder, etc.
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BS in computer science/machine learning, applied mathematics, statistics, engineering, or related fields. Serve as an independent subject matter expert for machine learning and computer vison.
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Experience with some of the following areas: Dashboard building, Cloud Computing, Natural Language Processing, Machine Learning, Platform Development, Networking, System Design, and/or Web Development.
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Implement HMI (Human-Machine Interface) and SCADA (Supervisory Control and Data Acquisition) systems. This position requires a deep understanding of automation, programming, industrial control systems, and database management for storing machine data.
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Job duties include but are not limited to; tearing down and repairing of gear boxes, motors, annealing cars or hoppers, prefabricating or refurnishing machine parts, welding, use of cutting torches, grinders and large/small hand tools.
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Manage and optimize Apache Spark pools for high-performance data processing tasks. Designs, develops, and implements ETL/ELT processes using Azure Data Factory, Synapse pipelines, Databricks Notebooks, Event Hub to build integrations from Saas sources such as Service Now, Workday, Dynamics CRM, and Eloqua.
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Experience with cloud-based machine learning services and platforms such as Google Cloud VertexAI or AWS SageMaker, and experience with model training, evaluation, and deployment workflows. Basic understanding of data preprocessing techniques such as feature scaling, feature engineering, and dimensionality reduction, and their application in preparing environmental data for machine learning models.
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Machinist apprentice will work towards being responsible for the maintenance, upkeep, repair and construction of equipment used in the casting and finishing of steel components used for railroad undercarriage support wheel assemblies.
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Experience with: Google Cloud Platform, Apache Beam and or Google Cloud Dataflow, Google Kubernetes Engine or Kubernetes. Experience with stream processing using Apache Kafka. Experience with: Google Cloud Platform, Apache Beam and or Google Cloud Dataflow, Google Kubernetes Engine or Kubernetes.
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Programming: You are proficient in Python or other high level programming language with experience in using geospatial and machine learning libraries (eg., OpenCV, TensorFlow, PyTorch etc). You will leverage background in remote sensing, image processing, statistical, geo-statistical and machine learning models to analyze complex imagery data to develop an scalable image processing pipeline.
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