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Experience in Data Science, machine learning algorithms and LLM is a preference. Familiarity with workflow management tool such as Apache Airflow. Experience with data visualization and business intelligence tools such as DOMO and Google Looker Studio.
$130,000 - $140,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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In-depth knowledge of Apache Spark, PySpark and Databricks architecture. Oversee the implementation of data processing workflows, analytics, and machine learning models using Databricks.
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Proven experience as a Technical Lead with a focus on Databricks and big data technologies on Azure Cloud Platform. Role: Azure DataBricks Tech Lead. Hands-on experience in writing python code, pyspark notebooks and Azure Cloud, Configure Databricks clusters and ensure adherence to best practices and coding standards.
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Demonstrated experience with data-oriented workflow orchestration tools within the Azure ecosystem, such as Azure Data Factory or Azure Logic Apps, or external tools like Apache Airflow, ML flow, or Argo, required.
$90,000 - $115,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Nice to have experience on Financial Domain on Online Banking and Fraud prevention detection by using Machine learning and Big Data Processing Technologies. - Experience with Apache Kafka for online data publishing and consuming.
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Design and implement scalable and efficient data processing architectures using Databricks. 8+ years of experience in Databricks. Technical Lead with 12+ yrs of experience as well as expertise in data engineering and analytics in.
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Run Server Architecture via Container : Docker Image for php-fpm, API-v2, Apache Docker Compose for php-fpm, API-v2, Apache GitLab CI/CD for Docker php-fpm, API-v2, Apach. Containers, Apache, PHP-FPM, VueJS, NodeJS, JavaScript, Python, GitLab CI/CD, HTML, CSS.
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Experience with tools, frameworks, and platforms such as AWS SageMaker, Bedrock, RAG, Apache Airflow, TensorFlow, or PyTorch is a plus. 2-5 years of industry experience as a Data Scientist/AI | Machine Learning engineer preferred.
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Knowledgeable of Client platform technologies including Apache Airflow, Kubernetes, Dask, Ray, and MLFlow. Design and implement frameworks and tools to streamline the machine learning process.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.
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Designing and implementing performance data movement pipelines using multiple ETL tools with batch and real-time event data streams (Databricks, Informatica, Apache Kafka, Azure Event Hub, AWS Kinesis, SQL Packages, etc.
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Experience in working with large-scale datasets and data processing frameworks like Apache Spark. Bedrock Expertise : Mastery of Bedrock, platform for MLOps (Machine Learning Operations.
$120,000 - $150,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Deep understanding of cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Apache Spark, Kafka) Implement advanced machine learning algorithms into practical, scalable applications that are integrated into broader systems.
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Knowledge of data storage and querying technologies like Amazon S3, Amazon Redshift, or Apache Spark. Familiarity with AWS services for large-scale data processing, such as Amazon Kinesis, Apache Kafka, or AWS Glue.
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