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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications. Strong programming skills in Python and Java; experience with Machine Learning libraries and frameworks.
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At least 4 years of experience in data engineering working with Big Data Technologies: Apache Spark, Pyspark, Hadoop, and DataBricks with delta lake. Experience with Apache Airflow, Hive, Snowflake, Kafka, Python.
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Utilize programming languages like Java, Python, SQL, Ruby and Go, Container Orchestration services including Docker and Kubernetes, CM tools including Ansible and Terraform, and a variety of AWS tools and services.
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In our Data science track we prepare you to get job as one of the following: Python developer, a data analyst, data visualization developer, a statistician, a machine learning engineer or a data scientist.
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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.
$247,000InternExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Your expertise in ETL, DataBricks, Python, Spark, Scala, JavaScript/JSON, SQL, and Jupiter Notebooks will be essential in ensuring efficient data processing and analysis. - High level of proficiency in ETL processes and demonstrated hands-on experience with technologies such as DataBricks, Python, Spark, Scala, JavaScript/ JSON, SQL, and Jupyter Notebooks.
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What you will be responsible forDevelop/ Build and enhance data pipelines using Python, Spark based data engineering solutions (Databricks), and SQL (AWS Redshift). Hands on development in Python, PL/SQL, SQL, Shell Scripting, AutoSys. Hands on experience working in cloud data platforms such as AWS Redshift, Spark based data engineering solutions.
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Demonstrated expertise in machine learning, deep learning, and NLP, with a strong portfolio in large language models like GPT-3, BERT, and RAG.Advanced proficiency in Python, with hands-on experience in ML libraries and frameworks such as TensorFlow and PyTorch.
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Leverage Databricks for data engineering, analytics, and machine learning tasks within application development. Proven experience as a Full Stack Developer with expertise in Angular, Java, microservices, Python, and Databricks.
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Proficiency in programming languages such as Python, R, or SQL. Strong knowledge of machine learning techniques, statistical analysis, and data visualization tools Tableau, Power BI.
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Design, develop and deliver scalable, robust and highly re-usable components using technologies such as Python, Java, AWS serverless (Lambda, Glue), Apache Spark, Apache Kafka and REST.
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Skills Required: Requires experience in the following: Agile SDLC; Application Architecture Disciplines; Jenkins; NodeJS; Spring; Java; Python; React; Shell Scripting; SQL; REST; Maven; Apache Ant; JSON; Apache Zookeeper; AWS Cloud Services; Oracle; Apache Spark; Splunk; GIT; Junit; Unit Testing; and User Acceptance Testing.
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Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka. Proficiency in data engineering tools and technologies - SQL, Python, Spark, DBT, Airflow, Kafka.
$138,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Frameworks & Tools: Extensive experience with Hibernate/JPA, AWS, Databricks, Angular/React JS, and JBOSS Enterprise SOA. Knowledge of Apache Kafka, Apache Spark, and ActiveMQ is a plus.
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Ideally you have an in-depth understanding of streaming data technologies like Amazon Kinesis or Apache Kafka, and experience with open-source data processing frameworks like Apache Spark, Apache Flink, or Apache Storm.
$151,300Full-timeExpandApply NowActive JobUpdated Today
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