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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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Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark. Solid understanding of foundational concepts and algorithms in statistics and machine learning, including NLP, linear/logistic regression, SVM, random forest, boosting, neural networks, dimensionality reduction, reinforcement learning, etc.
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Big Data & Distributed Systems : Hands-on experience with Apache Spark for distributed data processing, PySpark , or Spark MLlib for scalable machine learning.
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Apache Kafka, Apache Flink, Apache Spark, Trino (Presto), Apache Airflow/Dagster, Apache Superset, AWS S3, Snowflake, Amplitude, CDP (e.g. Segment.com) You will report into the Senior Director of Engineering, Data Platform as part of our Data organization in Engineering.
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3+ years of experience in batch and streaming ETL using Spark, Python, Scala, Snowflake, or Databricks for Data Engineering or Machine Learning workloads. Experience using machine learning in data pipelines to discover, classify, and clean data.
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Proficiency with deep learning tools and at least one machine learning tool, such as Hadoop, Apache Spark, TensorFlow, scikit-learn, or cloud-provider equivalents. Proven ability to work with at least one machine learning tool like Hadoop, Apache Spark, TensorFlow, or scikit-learn, or cloud-provider equivalents.
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Expérience avec les services infonuagiques de Microsoft Azure : Machine Learning, Databricks (ou Apache Spark), Data Factory et SQL Data Warehouse. Expérience avec les services infonuagiques de Microsoft Azure : Machine Learning , Databricks (ou Apache Spark), Data Factory et SQL Data Warehouse.
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BS in Computer Science, Data Analytics, Data Science, Information Systems, Information Technology, Mathematics, Electrical Engineering, Computer Engineering, or similar technology-related degree.
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We are hiring a talented Senior Data Engineer in roles related to building cloud-based data pipelines for machine learning, data processing with Apache Spark, and database development.
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Bachelor's degree in Computer Science, Data Engineering, Machine Learning, or a related field is required. Manage and build high-performance Data Engineering and Machine Learning Engineering teams, fostering a culture of innovation and excellence in a remote-first environment.
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Coaches and mentors others by example and through direct coaching on machine learning and artificial intelligence skills. Facilitates customer understanding of the impact of AI on their operating model and develops their skills in and comfort with machine learning solutions.
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Experience with data management technologies such as Databricks, Apache Spark, Hadoop, Kafka. The Senior Machine Learning Engineer will work on building AI/ML solutions across a wide range of business applications.
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This role requires a deep understanding of big data technologies, particularly Apache Spark, as well as expertise in data engineering and analytics. Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks.
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We are hiring talented Senior Data Engineers in roles related to building cloud-based data pipelines for machine learning, data processing with Apache Spark, and database development.
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ML | AI | Machine Learning | DevOps | Data & Analytics | Infrastructure | CI/CD | Terraform | Gitlab | Azure Devops | AWS | Azure | DataBricks | Ansible | Apache Spark | Kafka | Kubernetes | Docker | Linux.
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