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8+ years experience demonstrating an established track record in Data Engineering and Machine Learning; experience with GPUs as well as expertise in tuning and analyzing Apache Spark workloads.
$176,000 - $333,500 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Experience with Apache Airflow and Apache Spark; Spark performance turning. We are seeking a Senior Machine Learning Engineer to join DS&E. Candidates should possess robust knowledge and hands-on experience in end-to-end ML modeling, including design, development, deployment, monitoring, and maintenance, plus proficiency with cloud computing infrastructure, AWS in particular.
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Knowledge of cloud & computing technologies such as: Hadoop, Apache Spark, AWS, Microsoft Azure or Google cloud. Hybrid, 3 daysExperience with machine learning tools such as scikit-learn, R, Theano, TensorFlow, SparkML, or FoundryExperience in using two or more of the following modeling types to solve business problems: classification, regression, time series, clustering, text analytics, survival, association, optimization, reinforcement learning.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience with Machine Learning cloud technologies such as Azure Machine Learning (AML), AWS SageMaker or Spark ML. Experience with Big Data platforms such as Databricks or Apache Spark.
$66,000 - $185,000Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience with the Azure Ecosystem (Azure Data Lake, Azure Data Factory, Azure Databricks, Azure Machine Learning (AML), Azure Cognitive Services, Azure Storage) Design, build, test and maintain the Machine Learning platform supporting Data Science initiatives.
$66,000 - $185,000Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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We are currently seeking a Data Technical Lead (Apache Spark, Pyspark and Databricks) to join our team in Dallas , Texas (US-TX) , United States (US). In-depth knowledge of Apache Spark, Pyspark and Databricks architecture.
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Strong software development (preferably, Python) and experience working with libraries and packages related to data manipulation, statistical analysis, visualization, and machine learning algorithms and deep learning framework.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Experience with machine learning tools such as scikit-learn, R, Theano, TensorFlow, SparkML, or Foundry. Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas.
$79 - $80Full-timeExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Experience working with data technologies, such as Apache Spark, Kafka, dbt, and data warehouses, for handling large-scale datasets. We have a fast-growing team that’s distributed around the world, with offices in San Francisco and New York City. Our team has years of experience building and operating business-critical machine learning systems at leading tech companies like Uber, Google, Meta, Airbnb, Lyft, and Twitter.
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Familiarity with advanced statistical and machine learning techniques such as clustering, gradient boosting machines (GBM), support vector machines (SVM), neural networks (e.g., ANN, RNN, CNN), and other deep learning algorithms is a plus.
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And familiarity with relevant frameworks and libraries for AI and big data, such as TensorFlow, Apache Spark, Databricks or Snowflake. Strong background in artificial intelligence and machine learning, including experience with deep learning frameworks like TensorFlow or PyTorch, for evaluating advanced document processing algorithms and models.
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More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark, Delta Lake and MLflow.
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Experience with distributed or parallel programming frameworks, including Apache Spark or NVIDIA CUDA, and infrastructure as code (IaC) frameworks and services, including Terraform or CloudFormation.
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GCP Professional Machine Learning Engineer certification is required. Experience with distributed computing frameworks such as Apache Spark. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Strong programming skills with one or more languages such as Python, PySpark, Apache Spark, Java, JavaSript, C, C. Extensive experience using Snowflake, AWS SageMaker, GCP/GCP BigQuery, DBT, and Airflow for AI/ML model deployment and operationalization.
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