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Experience working with machine learning frameworks (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) and distributed big-data tools (e.g. Spark) is a plus. We're looking for someone who has a passion for building scalable machine learning and MLOps platforms using technologies such as Python, Databricks, Spark, AWS, Airflow, Terraform, etc.
$110,000 - $142,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Experience with data management technologies such as Databricks, Apache Spark, Hadoop, Kafka. As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications.
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Advanced experience with industry tools and platforms used to build scalable machine learning systems, such as Elasticsearch, Kubernetes, Docker, Redis, Apache Kafka, SQL, NoSQL, Infrastructure as Code (IaC), AWS Lambda, and/or Apache Spark.
$88,600 - $166,600Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications within The Friedkin Group of companies. Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP.
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Experience with Apache Airflow and Apache Spark; Spark performance turning. Familiar with PySpark dataframe and data processing libraries, machine learning frameworks (like Tensorflow, Keras or PyTorch), and other machine learning libraries.
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Plus, to be a Committer or PMC Member with the Apache Software Foundation on big data technologies: Apache Spark, Hadoop Stack, Kafka, Comet, Atlas, delta. We use various open-source technologies (such as Apache Spark, Presto, Comet, Apache Airflow to name a few) to develop services for Adobe customers and partners.
$154,000 - $278,800 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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As a member of the Data Engineering team, the Machine Learning Engineer will work closely with business domain experts and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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Architect and develop large-scale, distributed data processing pipelines using technologies like Apache Spark, Apache Beam, and Apache Airflow for orchestration. Proven expertise in Apache Spark, Apache Beam, and Airflow, with a deep understanding of distributed computing and data processing frameworks.
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We are currently seeking an experienced Machine Learning Engineer to join the Big Data and Advanced Analytics department. Knowledgeable of various machine learning frameworks, libraries, and packages including Scikit-learn, TensorFlow, Keras, and PyTorch.
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Proven proficiency in data pipeline tools (e.g., Apache Airflow, Apache Kafka, Apache Spark) - Familiarity with machine learning and AI platforms. Extensive experience with data warehousing and data lake technologies (e.g., Snowflake, BigQuery, Redshift.
$140,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Engineer will work closely with Business domain experts and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics, machine learning, and artificial intelligence.
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It leverages technologies like robotic process automation (RPA), machine learning, natural language processing, and blockchain to help its clients enhance operational efficiency, improve customer experience, and drive business growth.
$65 - $70 an hourFull-timeExpandApply NowActive JobUpdated 27 days ago - UpvoteDownvoteShare Job
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Hands on experience with Big Data technologies such as Apache Hadoop, Apache Spark, and Apache Kafka, as well as experience with data pipeline orchestration tools such as Apache Airflow, experience with Infrastructure as a Code tools such as Terraform.
$125,000 - $203,000Full-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Title: Senior Machine Learning Engineer. Research and prototype new technologies to advance the machine learning capability. Design and implement frameworks and tools to streamline the machine learning process.
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Collaborate with data scientists and engineers to design, build, and maintain Azure-based MLOps pipelines for automating machine learning model deployment, monitoring, and maintenance. Implement Azure-based deployment pipelines for deploying machine learning models into production environments.
$135,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated Today
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