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Implement robust data streaming pipelines using technologies like Apache Flink and Kafka. Collaborate with teams to embed machine learning models into streaming workflows. Implement robust data streaming pipelines using technologies like Apache Flink and Kafka.
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Distributed data processing in Hadoop, Spark, BigQuery, or Apache Beam. The Mercedes-Benz Data and AI team is seeking a hands-on machine learning expert for research, design, and development of cutting-edge technology applied in projects that will shape the future of Mercedes-Benz vehicles with the goal of enhancing our customer’s experience.
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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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Experience with streaming technologies such as Apache Flink, Samza, DataFlow is desired. Effortlessly run advanced AI and machine learning with cloud-scale data and compute. Experience with streaming technologies such as Apache Flink, Samza, DataFlow is desired.
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Hands-on experience in building large scale data processing and retrieval systems and pipelines: Apache Spark, Apache Beam, Google Cloud Dataflow, AWS Data Pipeline, Faiss, etc. This spans areas from performant onboard real-time systems to highly scalable offboard systems that deliver data to power Perception's machine learning (ML) models, diverse ML task evaluation, foundational model development, and commercialization.
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Proficient in using any of the following open-source tools: TensorFlow, PyTorch, Scikit-Learn, Keras, Apache Spark, and Caffe. Apply state-of-the-art machine learning and deep learning technologies to analyze the app experience of TikTok users and develop algorithms to provide the best experiences.
$355,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Industry experience using distributed data processing such as Spark, BigQuery, or Apache Beam. Experience with machine learning or deep learning related toolset/frameworks, such as Pandas, Numpy, Scikit-learn, TensorFlow, PyTorch, etc.
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Build a modular set of data services using Python, SQL, AWS Glue, Lambda, API Gateway, Kafka, data build tool (dbt), Apache Spark on EMR, among others. Familiarity with machine learning and data science ecosystems especially AWS Sagemaker and Databricks is highly preferred.
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Big data processing technologies like Apache Spark. Stay updated with industry trends and best practices in machine learning and artificial intelligence. Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related field with 5+ years experience as a Software Engineer , or similar role.
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Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) and tools for data processing (e.g., Apache Spark). As a Machine Learning Engineer specializing in recommendation systems, you will play a pivotal role in shaping and enhancing our personalized content delivery platform.
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Experience with Big Data tools and ETL frameworks (Hadoop, Hive, Presto, Spark, Scala, Apache Airflow, etc.) Experience with machine learning platform for search & discovery related rankings is a strong plus.
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Hands-on experience working with large data sets using Hadoop or Apache Spark. Masters or PhD in Data Science, Machine Learning, Computer Science, Statistics, Mathematics or a related field.
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Founded by the original creators of Apache Spark, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world’s toughest problems. Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way.
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