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Our data science stack includes AWS EMR, Apache Spark (core, mllib, and streaming), Elasticsearch and raw Lucene, scikit-learn, and more. If you have industry experience developing production software for machine learning, especially in areas like recommendation engines, natural language processing, and deep learning for text data, we'd love to talk to you.
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New York City (Hybrid On-Site): $165,100 - $188,500 for Senior Machine Learning EngineerSan Francisco, California (Hybrid On-Site): $174,900 - $199,700 for Senior Machine Learning EngineerRemote (Regardless of Location): $140,000 - $159,800 for Senior Machine Learning Engineer.
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Proficient in Apache Hadoop, Map-reduce, Apache Spark, and in messaging Systems as Kafka. Knowledge and/or experience in Data mining, Machine Learning, Image and Video Processing.
$286,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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6+ years of proven experience as a technical product manager, data scientist, data engineer, machine learning engineer, or similar role. RAPIDS, the open-source suite of accelerated data science libraries and primitives, brings accelerated computing to the wider analytics world by combining the performance of NVIDIA GPUs with the ease of use of Python, Apache Spark, and modern C.
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Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow, and similar related technologies. Experience with scientific libraries in Python (numba, pandas) and machine learning tools and frameworks (scikit-learn, tensorflow, torch, etc.
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Experience and knowledge in deploying machine learning at scale on big data platforms (e.g., PySpark with Apache ecosystem, AWS EMR). Proven track record in industry solving real-world problems as a Machine Learning Engineer, Data Scientist, Data Engineer, or similar role.
$250,000 a yearFull-timeExpandApply NowActive JobUpdated 26 days ago - UpvoteDownvoteShare Job
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Apache Spark, Airflow, Trino, Pinot, Flink, KafkaData Warehousing and Data Lake technologies such as Snowflake, Databricks, various table formats such as Iceberg or Delta Lake. The adjacent areas of major focus are Machine Learning Infrastructure and workflow, Experimentation Platform, Knowledge Graphs and various Data Science and Analytics related tooling.
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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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Strong familiarity (and ample hands-on experience) with the Apache Hadoop ecosystem: Spark, Kafka, Hive/Iceberg/Delta Lake, Presto/Trino, Pinot, etc. Setting ourselves apart, we also make it easy for all customers to utilize the platform for batch and streaming analytics, machine learning and threat hunting through the production and delivery of self-service platforms (Query Platform, Analytics Platform, Enrichment platform.
$300,000 a yearFull-timeRemoteExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Coactive was founded by experts who shaped the fields of high-performance deep learning and data-centric AI. We have the scars from building and working with the first generation of modern machine learning systems at Google, Meta, Pinterest, eBay, Lyft, and other leading organizations.
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Build data processing systems on AWS technologies (e.g., S3, EC2, EMR) and Apache Spark to process petabytes of data. Customer Behavior Analytics' Downstream Impact (DSI) team owns Causal Machine Learning products aimed at estimating long-term value and informing financial planning.
$223,600 a yearFull-timeExpandApply NowActive JobUpdated 10 days ago - UpvoteDownvoteShare Job
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Experience with big data, including Apache Spark and Hadoop. Solid understanding of Machine Learning algorithms and Natural Language Processing methods. Hands-on experience with scalable machine learning techniques applied to both structured and natural language data.
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Experience working with Apache Hadoop, Databricks and related technology stack like Hive, Presto etc. Knowledge of Data Science, Machine Learning, Statistical modeling techniques and data mining concepts is desirable.
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Distributed data processing in Hadoop, Spark, BigQuery, or Apache Beam. MBRDNA is headquartered in Silicon Valley, California, with key areas of Autonomous Driving, Advanced Interaction Design, Digital User Experience, Machine Learning, Customer Research, and Open Innovation.
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Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.
$204,300 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago
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