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Big Data: Apache Spark, YARN, Livy, ZooKeeper, Ranger, Knox, Polybase. Machine Learning: SparkSQL, Java, Scala, Python, Jupyter. Big Data: Apache Spark, YARN, Livy, ZooKeeper, Ranger, Knox, Polybase.
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Develop and adjust benchmarking suites and methodologies for various software technologies such as Java, Golang, open-source database, Apache Kafka, and machine learning applications. Deep understanding of Linux kernel, compilers, middleware technologies (Java, Golang, TensorFlow, PyTorch), and container environments (Kubernetes, Docker.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Packages:Experience with building and optimizing machine learning pipelines using tools like Apache Airflow, Kubeflow, or MLflow. Experience with cloud platforms (e.g., AWS, Azure, GCP, OCI) and their machine learning services.
$96,800 - $251,600 a yearFull-timeExpandApply NowActive JobUpdated 12 days ago - UpvoteDownvoteShare Job
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Excellent programming and algorithmic skills - Are proficient with Python and experience with data processing tools (e.g., SciPy, NumPy, Pandas, PyTorch, and Apache Spark) As a Senior Machine Learning Engineer, you will develop cutting-edge algorithms for consumer product development.
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As a Sr Machine Learning Engineer specializing in Language and Multimodal Models at Dahlia Labs, you will lead our AI development efforts. Drive research initiatives on cutting-edge machine learning algorithms, with a strong emphasis on NLP / NLU and multimodal technologies, to keep Dahlia Labs at the forefront of retail AI.
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Expertise at building highly scalable frameworks for processing streaming data and query/result pipelines for end user and machine-driven query processing Experience with open-source technologies like Linux, Apache/Tomcat, and MySQL Strong written and verbal communication skills Experience with relational databases and SQL Experience writing scalable REST APIs Highly desired: Experience with any modern search engine (Elasticsearch, solr, etc.
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Experience with graph-based data workflows such as Apache Airflow, Meson. The vision of the Machine Learning (ML) Engineering team at Disney is to drive and enable ML usage across several domains in heterogeneous language environments and at all stages of a project s life cycle, including ad-hoc exploration, preparing training data, model development, and robust production deployment.
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Additional expertise in application specific benchmarks for databases, event streaming, Golang, etc would be beneficial. Analyze application performance across various hardware components (CPUs, GPUs, storage and memory subsystems) in both virtual machines and bare metal in order to optimize for cost, performance and utilization.
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More than 10,000 organizations worldwide including Comcast, Cond 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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2 years of experience in: Processing Big data using BigQuery and Apache Hive; Building deep learning models using Pytorch and Tensorflow; and Building and using different types of neural networks, such as Recurrent Neural Networks (RNN), Convolutional Neural Networks (CNN), or Graph Neural Networks (GNN.
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Work at the core of OpenSearch and Apache Lucene open source software with opportunities to contribute to open source. Work on challenging problems in areas such as data storage, query optimization, JVM performance optimization, security, machine learning and more.
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Our backend teams span many domains, from our core compute fabric resource management infrastructure, to service platforms, to machine learning infrastructure. Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way.
$157,700 - $213,800 a yearFull-timeExpandApply NowActive JobUpdated 5 months ago - UpvoteDownvoteShare Job
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Deep understanding of Linux kernel, compilers, middleware technologies (Java, Golang, TensorFlow, PyTorch), and container environments (KClientnetes, Docker). Should have Linux OS knowledge, programming knowledge on golang, java, python.
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Experience with building and optimizing machine learning pipelines using tools like Apache Airflow, Kubeflow, or MLflow. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform, OCI) and their machine learning services.
$96,800 - $251,600 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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Familiarity with Apache Spark. The ideal candidate will have strong software engineering, data engineering, and machine learning skills, which will align successfully with the organization.
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