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Architect and implement big data processing solutions leveraging Apache Spark for ETL, data transformation, and machine learning workflows. Expertise in Databricks, Apache Spark, and big data technologies.
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Senior Machine Learning Engineer (Python, Spark, MLOPS, Cloud) New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning Engineer. As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.
$165,100 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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San Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning Engineer. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure.
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Familiarity with machine learning frameworks (e.g., scikit-learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Experience with big data technologies (e.g., Hadoop, Spark.
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This could include setting up data pipelines, using cloud-based machine learning services, or working with big data technologies (e.g. Hadoop, Spark). Machine Learning Models: building and deploying machine learning models.
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Required Skills & Experience 3+ years of Data Engineering experience Jav SQL NoSQL Database experience Python AWS Spark, Kafka, or Flink Desired Skills & Experience Masters degree or higher in Computer Science or related field.
$145,000 - $175,000Full-timeRemoteExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Good understanding of machine learning pipelines and machine learning frameworks such as TensorFlow and PyTorch. Design, develop, debug, and modify components of machine learning and deep learning systems and applications, including data/ETL and feature engineering pipelines.
$79 - $79.37Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience with common data science and ML frameworks, such as numpy, pandas, Spark, scikit-learn, TensorFlow, and PyTorch. The successful candidate will have extreme intellectual curiosity, perseverance, good academic knowledge of machine learning models, statistical techniques and will demonstrate strong programming and large-scale data engineering skills.
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Big data - Hive, Spark, Hadoop, queuing systems like Apache Kafka/Rabbit MQ/AWS Kinesis. ZS's Scaled AI practice is part of ZS's rich and advanced AI ecosystem, in the Architecture & Engineering Expertise Center, focused on creating continuous business value for clients using a range of innovative machine learning, deep learning, and engineering capabilities.
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Experience advising stakeholders on best practice related toTechnologyprocesses and solutionsPreferred:Experience in projects and processes related to corporate law department operations and technologyExperience in configuring and integrating CLM solutions such as Agiloft, Ironclad and DocuSign a plus, but candidates with the appropriate business knowledge who are very proficient at learning and adopting complex systems would also be considered for this role.
$193,750 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Architect and implement big data processing solutions using Databricks, leveraging Apache Spark for data transformation, ETL processes, and machine learning workflows. Proficiency in Databricks, Apache Spark, and related big data technologies.
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3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. The search team comprises the e-commerce search platform, backend services, machine learning endpoints, and our search engine, which enables grainger.com customers to findproducts that serve relevant content to online customers, internal support teams, and marketing programs.
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There are numerous scientific and technical challenges you will get to tackle in this role, such as deep learning techniques and natural language processing to abstract sequences and embeddings from customer features, offer/content features.
$260,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (Apache Beam, Hadoop, Spark, Hive.
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The Data Science Solutions Consultant Sr. will develop and deploy artificial intelligence and machine learning models in production in on-premises and cloud enablement. Three (3) years of experience delivering projects using Spark, Python and other Big Data technologies in Hadoop ecosystem.
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