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Experience in technologies such as Hadoop, Spark, Kafka, Redis, Cassandra, Pandas, Dask, Airflow, Apache Beam, MongoDb, Hive, Impala, Hazelcast, Athena, Presto. Plus: Experience in Kubernetes, Kubeflow, Docker, and container technologies, as well as infrastructure as code and CI/CD technologies.
ExpandApply NowActive JobUpdated 6 days ago - UpvoteDownvoteShare Job
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Preferred Experience with REST/gRPC, Kubernetes, AWS, Azure, Grafana, Kibana, Elastic, Airflow. Develop, and maintain robust and scalable backend applications using Node, JAVA, Python on Kubernetes and Docker.
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Preferred Experience with REST/gRPC, Kubernetes, GraphQL, AWS, Azure, Grafana, Kibana, Elastic, Airflow. Develop, and maintain robust and scalable backend applications using JAVA on Kubernetes and Docker.
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Hands-on Experience in Big Data tools, using Hadoop, Kafka, Spark, Presto, Airflow, Elastic Search, Docker and Kubernetes. Hands-on Experience in Big Data tools, using Hadoop, Kafka, Spark, Presto, Airflow, Elastic Search, Docker and Kubernetes.
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To do so, we leverage the internal big data platform that is built on top of AWS, S3, Spark, Presto and data science tools such as Jupyter notebooks, Pandas, Bokeh, Superset and Airflow. Experience in devops, i.e. Linux, Ansible, Docker, Kubernetes.
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Experience with cloud technologies in AWS or GCP as well as container systems such as Docker or Kubernetes. Familiarity with orchestration tools such as Apache Airflow or AWS step functions.
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Familiarity with containerization and workflow orchestration systems, e.g. Docker, Kubernetes, Airflow, Flyte. Familiarity with containerization and workflow orchestration systems, e.g. Docker, Kubernetes, Airflow, Flyte.
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Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and containerization (e.g., Docker, Kubernetes). Experience with data pipeline and workflow management tools: AWS glue, Airflow, etc.
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Experience with Docker, Git and AWS (EC2, ECS, S3, Step Functions, and Athena). Experience with tools including Meltano, dbt, Airflow, and Superset is required. Advanced experience with ETL pipelines, data modeling and managing data warehouses (Snowflake, BigQuery, Redshift, etc.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Experience with Kubernetes, Docker, and Airflow is a plus. Experience with Kubernetes, Docker, and Airflow is a plus. Join the Affirm team as a Senior Machine Learning Engineer and contribute to the success of our ML Underwriting team.
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Experience with tools like mlFlow, Airflow , Docker and Cloud Platforms such as AWS/GCP is ideal. Experience with tools like mlFlow, Airflow , Docker and Cloud Platforms such as AWS/GCP is ideal.
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To do so, we leverage our internal data platform built on top of AWS, S3, Spark, Trino using open source data science tools such as Jupyter notebooks, Pandas, Bokeh, Superset, and Airflow. Experience with devops tools - e.g., Linux, Ansible, Docker, Kubernetes.
$104,000 - $348,000 a yearFull-timeExpandApply NowActive JobUpdated 4 months ago - UpvoteDownvoteShare Job
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We work in the ML training and deployment ecosystem, you will be embedded within the Automated Driving & ADAS team and work directly with Autonomy ML engineers to accelerate development and deployment of ML models.
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Salesforce is looking for an exceptional Machine Learning Engineer| AI Resercher to help us take on one of the world’s most extensive data sets and transform it into amazing products that feel like magic.
$133,800 - $258,700 a yearFull-timeExpandApply NowActive JobUpdated Yesterday
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